What is SDLC?
The foundational framework every IT project follows � from idea to live software and beyond.
Definition
The Software Development Life Cycle (SDLC) is a systematic, structured process that defines the tasks performed at each stage of software development. It provides a framework for planning, creating, testing, deploying, and maintaining software applications.
SDLC is not a single methodology � it is the umbrella concept that covers ALL approaches to building software, whether a team uses Waterfall, Agile, DevOps, or any other methodology. Every software project, from a simple mobile app to a massive banking system, follows some form of SDLC.
The 7 Phases of SDLC
Every software project moves through these seven phases. Some phases overlap, some repeat (in Agile), but the sequence is always the same conceptually:
Planning
Scope, feasibility, resources
Requirements
Gather & document needs
Design
Architecture & UI/UX
Development
Write code
Testing
Verify quality
Deployment
Release to production
Maintenance
Bug fixes & updates
Why SDLC Matters for Your Daily Work
When you understand SDLC, you can do five things that separate a competent IT recruiter from a beginner:
- Read a JD and instantly know what phase the role belongs to. A "Solutions Architect" works in Design (Phase 3). A "QA Automation Engineer" works in Testing (Phase 5). A "DevOps Engineer" works in Deployment (Phase 6).
- Predict what other skills the candidate should have based on the phase. A developer (Phase 4) should know version control (Git), testing frameworks, and CI/CD basics � even if the JD doesn't list them.
- Ask intelligent screening questions that demonstrate domain knowledge: "What SDLC methodology does your current team follow? How long are your sprints?"
- Differentiate between similar-sounding roles � a "QA Analyst" (manual testing) is very different from an "SDET" (writes test automation code), even though both work in Phase 5.
- Understand why the client needs specific tools or certifications � a client asking for "Terraform experience" needs someone who works in Deployment/Infrastructure (Phase 6), not a frontend developer.
SDLC Models � How Teams Actually Work
Different companies use different SDLC models. The model a company uses affects the types of roles they hire for and the skills they require. Here are the five most common models you will encounter:
How it works: Each phase must be 100% complete before the next phase begins. Requirements are fully documented upfront, then design, then development, then testing, then deployment. No going back.
Where you will see it: Government contracts, banking systems, healthcare/pharma (regulated industries where documentation and compliance are critical), defense/military projects.
JD signals: "Waterfall experience required," heavy emphasis on documentation roles (Business Analyst, Project Manager), references to "phase gates," "sign-off processes," or "V-model."
Recruiter impact: Waterfall projects hire in phases � they need BAs first, then architects, then developers, then QA. You may see large batches of QA requests after development completes.
How it works: Work is divided into short cycles called "sprints" (typically 2 weeks). Each sprint delivers a working piece of software. Teams are cross-functional (developer + QA + designer work together). Daily 15-minute standups, sprint planning, sprint reviews, and retrospectives.
Where you will see it: Most modern tech companies, SaaS products, startups, digital transformation projects, product companies. Roughly 70-80% of IT job descriptions reference Agile.
JD signals: "Agile environment," "Scrum," "sprint planning," "user stories," "product backlog," "retrospective." Roles: Scrum Master, Product Owner.
Key terms to know:
- Sprint: A fixed time period (usually 2 weeks) where a set of features is built, tested, and delivered.
- Standup / Daily Scrum: A 15-minute daily meeting where each team member shares: What did I do yesterday? What will I do today? Any blockers?
- Product Backlog: The full list of features, bugs, and tasks prioritized by the Product Owner.
- Sprint Review: Demo of completed work to stakeholders at the end of each sprint.
- Retrospective: Team reflection on what went well, what didn't, and how to improve.
- Story Points: A way to estimate effort/complexity of work items (not hours, but relative difficulty).
How it works: No fixed sprints. Work flows continuously through stages: To Do ? In Progress ? Code Review ? Testing ? Done. Work-in-progress (WIP) limits prevent overloading the team. Visual board (physical or digital) shows all work items and their status.
Where you will see it: DevOps teams, support/maintenance teams, continuous delivery environments, operations teams. Often combined with Scrum ("Scrumban").
JD signals: "Kanban board," "continuous delivery," "WIP limits," "flow optimization," "lean methodology."
How it works: SAFe scales Agile practices across large organizations with hundreds of developers. Multiple Agile teams are coordinated through an "Agile Release Train" (ART). Program Increments (PI) are 8-12 week planning cycles. PI Planning is a 2-day event where all teams align on objectives.
Where you will see it: Fortune 500 companies, large IT departments (100+ developers), government agencies adopting Agile at scale.
JD signals: "SAFe Agilist," "SAFe certification (SA, SPC, RTE)," "PI Planning," "Agile Release Train," "Program Increment," "Solution Train."
How it works: DevOps is both a culture and a set of practices that merges software development (Dev) with IT operations (Ops). The goal is to shorten the development lifecycle through automation: automated builds, automated testing, automated deployments. "Infrastructure as Code" means servers are configured by scripts, not manually.
Where you will see it: Cloud-native companies, SaaS products, platform engineering teams, SRE (Site Reliability Engineering) teams.
JD signals: "CI/CD," "Jenkins," "Docker," "Kubernetes," "Infrastructure as Code," "Terraform," "GitOps," "SRE," "platform engineering."
SDLC Phases � Deep Dive
Each phase produces specific deliverables, uses specific tools, and employs specific roles. Understanding this lets you connect JD requirements to the right phase.
Phase 1: Planning
The Planning phase is where the project is conceived and evaluated. Before any code is written, the organization decides whether the project should be built, how much it will cost, who will work on it, and when it will be delivered.
Activities in this phase:
- Feasibility Study: Can we build this technically? Can we afford it? Will it provide ROI? Three types: Technical feasibility, Economic feasibility, Operational feasibility.
- Resource Estimation: How many developers, QA engineers, architects do we need? What skill sets? This is where staffing requests originate � the client determines they need X number of Java developers for Y months.
- Timeline & Milestones: When will each phase start and end? What are the key milestones? What are the dependencies?
- Risk Assessment: What could go wrong? Technology risks, staffing risks, schedule risks, budget risks. Each risk gets a mitigation plan.
- Vendor/Contractor Selection: If the company uses external staffing vendors (like our agency), this is when they issue requisitions and select partners.
Key Roles:
Project Manager, Program Manager, Product Owner, CTO/VP of Engineering, PMO Director.
Tools:
Jira, Microsoft Project, Confluence, Smartsheet, Monday.com, Asana, Gantt charts.
Key Deliverables:
Project Charter, Project Plan, Resource Plan, Risk Register, Budget Approval.
Phase 2: Requirements Gathering & Analysis
The Requirements phase is about understanding what the software must do. This is where Business Analysts, Product Managers, and Subject Matter Experts work together to document every feature, function, and constraint.
Activities:
- Stakeholder Interviews: Meet with business users, executives, and end users to understand their needs, pain points, and expectations.
- Business Requirements Document (BRD): A high-level document that describes the business problem, objectives, and desired outcomes. Written in business language, not technical language.
- Functional Requirements Document (FRD): A detailed document that specifies exactly what the software must do � every button, every screen, every calculation, every validation rule.
- User Stories: In Agile teams, requirements are written as user stories: "As a [user], I want to [action], so that [benefit]." Each story has acceptance criteria that define when it's complete.
- Use Cases & Process Flows: Visual diagrams showing how users interact with the system. "User clicks Login ? System validates credentials ? If valid, redirect to dashboard ? If invalid, show error message."
- Non-Functional Requirements: Performance (page must load in under 2 seconds), security (data must be encrypted), scalability (must support 10,000 concurrent users), availability (99.9% uptime).
Key Roles:
Business Analyst (BA), Systems Analyst, Product Manager, Product Owner, Subject Matter Expert (SME), UX Researcher.
Tools:
Jira, Confluence, Microsoft Visio, Lucidchart, Balsamiq (wireframes), Miro (collaborative diagramming), SQL (for data analysis).
Key Deliverables:
BRD, FRD, SRS (Software Requirements Specification), User Stories with Acceptance Criteria, Use Case Diagrams, Process Flow Diagrams.
Phase 3: Design
The Design phase translates requirements into a technical blueprint. Architects and designers decide how the software will be built � what technologies to use, how components connect, what the database looks like, and what the user interface looks like.
Two Levels of Design:
High-Level Design (HLD)
Also called: System Architecture, Solution Architecture
What it covers: Overall system structure � which components exist, how they communicate, which technologies are used, how data flows between systems.
Example: "The system will have a React frontend, a Java/Spring Boot backend with microservices architecture, a PostgreSQL database, deployed on AWS using ECS containers, with Redis for caching."
Who creates it: Solutions Architect, Technical Architect, Chief Architect
Low-Level Design (LLD)
Also called: Detailed Design, Component Design
What it covers: Specific implementation details � class diagrams, database table structures (schema), API endpoint specifications, data models, algorithm logic.
Example: "The User table has columns: id (UUID), email (varchar 255), password_hash (varchar 255), created_at (timestamp), is_active (boolean). The /api/users endpoint accepts GET/POST and returns JSON."
Who creates it: Technical Architect, Senior Developers, Database Architect, Lead Engineers
UI/UX Design:
In parallel, UI/UX Designers create wireframes (basic layout sketches), mockups (detailed visual designs), and interactive prototypes (clickable demos). They define the design system � colors, fonts, button styles, spacing � that ensures consistency across the application. Tools include Figma (most popular), Sketch, Adobe XD, and InVision.
Key Roles:
Solutions Architect, Technical Architect, UI/UX Designer, Database Architect, Security Architect, Lead Developer.
Key Deliverables:
HLD Document, LLD Document, Database Schema, API Specifications (Swagger/OpenAPI), Wireframes & Mockups, Design System, Security Architecture Document.
Phase 4: Development (Coding)
In the Development phase, the technical team writes the actual application code based on the design documents. This includes:
- Frontend Development: Building the user interface � what users see and interact with in their browser or mobile device. Technologies: React, Angular, Vue.js, HTML, CSS, JavaScript/TypeScript.
- Backend Development: Building the server-side logic � business rules, data processing, API endpoints, authentication. Technologies: Java/Spring Boot, Python/Django, Node.js, C#/.NET, Go.
- Database Development: Creating tables, writing queries, building stored procedures, setting up data relationships. Technologies: PostgreSQL, MySQL, Oracle, MongoDB, Redis.
- API Development: Building the interfaces that allow different parts of the system (and external systems) to communicate. REST APIs, GraphQL, gRPC.
- Integration: Connecting the application to third-party services � payment gateways, email services, analytics tools, CRM systems.
- Code Reviews: Developers review each other's code for quality, security, and best practices before merging into the main codebase.
- Unit Testing: Developers write automated tests for their own code to verify individual functions work correctly.
Key Roles:
Software Engineer/Developer, Frontend Developer, Backend Developer, Full Stack Developer, Mobile Developer (iOS/Android), Data Engineer, Database Developer/DBA, API Developer, Technical Lead.
Tools:
IDEs (VS Code, IntelliJ IDEA, Eclipse), Git/GitHub/GitLab/Bitbucket, Jira, Slack, Docker, Postman (API testing during development).
Phase 5: Testing (Quality Assurance)
The Testing phase verifies that the software works correctly, performs well, and is secure. QA teams execute tests at multiple levels to catch bugs before the software reaches end users.
Types of Testing (from smallest to largest scope):
| Test Type | What It Tests | Who Does It | Tools |
|---|---|---|---|
| Unit Testing | Individual functions/methods in isolation | Developers (during Phase 4) | JUnit, TestNG, pytest, Jest |
| Integration Testing | Two or more modules working together | Developers + QA | Postman, REST Assured, Spring Test |
| System Testing | The complete application end-to-end | QA Team | Selenium, Cypress, Playwright |
| UAT (User Acceptance Testing) | Business users verify the system meets requirements | Business Analysts + End Users | Manual testing, Jira for tracking |
| Performance Testing | Speed, scalability, stability under load | Performance Engineers | JMeter, LoadRunner, Gatling, k6 |
| Security Testing | Vulnerabilities, penetration testing, compliance | Security Engineers/Pen Testers | Burp Suite, OWASP ZAP, Nessus |
| Regression Testing | Existing features still work after new changes | QA Automation Engineers | Selenium, Cypress, automated suites |
Key Roles:
QA Analyst (Manual), QA Engineer (Automation), SDET (Software Developer Engineer in Test), Performance Engineer, Test Architect, Test Manager.
Phase 6: Deployment
Deployment means releasing the software to production � making it available to real end users. In modern organizations, deployment is largely automated through CI/CD pipelines.
Key Concepts:
- CI/CD Pipeline: Continuous Integration (automatically build & test code when developers commit changes) + Continuous Delivery/Deployment (automatically deploy tested code to production). Tools: Jenkins, GitHub Actions, GitLab CI, Azure DevOps, CircleCI, ArgoCD.
- Environments: Code moves through multiple environments before reaching production: Development (Dev) ? Quality Assurance (QA) ? Staging (Pre-Production) ? Production (Live).
- Containerization: Applications are packaged in Docker containers � self-contained units that include the code and all its dependencies. This ensures the application runs the same way in every environment.
- Orchestration: Kubernetes (K8s) manages hundreds or thousands of containers � starting them, stopping them, scaling them up/down, distributing traffic.
- Infrastructure as Code (IaC): Servers, networks, and cloud resources are defined in code files (Terraform, CloudFormation) rather than configured manually. This makes infrastructure reproducible and version-controlled.
Key Roles:
DevOps Engineer, Site Reliability Engineer (SRE), Release Manager, Cloud Engineer, Platform Engineer, Infrastructure Engineer.
Phase 7: Maintenance & Operations
After deployment, the software enters its longest phase � ongoing maintenance. This includes fixing bugs, applying security patches, optimizing performance, adding new features, and keeping the system running 24/7.
Activities:
- Bug Fixes: Users report issues ? triage ? fix ? test ? deploy patch.
- Security Patches: When vulnerabilities are discovered in libraries or frameworks, updates must be applied quickly.
- Performance Tuning: Database query optimization, caching improvements, server scaling.
- Monitoring & Alerting: Continuous monitoring of application health � response times, error rates, CPU/memory usage. Automated alerts when something goes wrong.
- Incident Management: When the system goes down, an incident response team follows a structured process: detect ? triage ? mitigate ? resolve ? post-mortem.
- L1/L2/L3 Support Tiers: L1 = basic troubleshooting (password resets, known issues). L2 = deeper technical investigation. L3 = engineering-level problem solving and code fixes.
Key Roles:
Production Support Engineer, Application Support Analyst, SRE, L1/L2/L3 Support Engineers, Systems Administrator, DBA (Database Administrator).
Tools:
ServiceNow (ticketing), PagerDuty (incident management), Datadog/New Relic/Prometheus+Grafana (monitoring), Splunk/ELK Stack (log analysis), Jira (bug tracking).
IT Roles & Job Title Taxonomy
A structured mental model for categorizing the 30+ IT roles you will encounter in US staffing requisitions.
Why This Matters
The IT industry uses hundreds of job titles, and many overlap or mean different things at different companies. A "Software Engineer" at Google might do the same work as a "Developer" at a bank or a "Programmer" at a government contractor. This module creates a structured mental model so you can instantly categorize any role you encounter.
Development Roles � The Core of IT Hiring
| Job Title | What They Actually Do | Key Skills on JDs | Seniority Ladder |
|---|---|---|---|
| Software Engineer / Developer | Write application code, build features, fix bugs, participate in code reviews, write unit tests. The most common IT title. | Java, Python, C#, JavaScript/TypeScript, Git, REST APIs, SQL, unit testing frameworks | Junior (0-3yr) ? Mid (3-6yr) ? Senior (6-10yr) ? Staff (10-14yr) ? Principal (14+yr) |
| Frontend Developer | Build the user-facing part of web applications � everything users see and interact with in their browser. Implements designs from Figma/Sketch into working code. | React / Angular / Vue.js, HTML5, CSS3, JavaScript/TypeScript, Webpack/Vite, responsive design, accessibility (WCAG) | Junior ? Mid ? Senior ? Lead Frontend ? Staff Frontend |
| Backend Developer | Build server-side logic � APIs, business rules, data processing, authentication, database interactions. The "brain" behind the application. | Java/Spring Boot, Python/Django/Flask, Node.js/Express, C#/.NET, Go, PostgreSQL, Redis, Kafka, REST/GraphQL APIs | Junior ? Mid ? Senior ? Staff Backend ? Principal |
| Full Stack Developer | Works on BOTH frontend AND backend. Owns features end-to-end. Common in startups and smaller teams where one person handles everything. | Must have BOTH: a frontend framework (React/Angular/Vue) + a backend language (Node.js/Java/Python). Also: databases, APIs, Git. | Junior ? Mid ? Senior ? Lead Full Stack |
| Mobile Developer | Build native or cross-platform mobile applications for iOS and/or Android devices. | iOS: Swift, SwiftUI, Xcode, UIKit. Android: Kotlin, Jetpack Compose, Android Studio. Cross-platform: React Native, Flutter, Dart. | Junior ? Mid ? Senior ? Lead Mobile |
| Embedded / IoT Engineer | Write software for hardware devices � firmware, sensors, real-time systems, industrial controllers, medical devices. | C, C++, RTOS (FreeRTOS, VxWorks), ARM processors, MQTT, embedded Linux, circuit design awareness | Junior ? Senior ? Staff ? Principal (niche, high rates) |
Data, Analytics & AI/ML Roles
| Job Title | What They Actually Do | Key Skills | How to Distinguish |
|---|---|---|---|
| Data Analyst | Query existing data to find insights, build dashboards and reports, answer business questions with data. | SQL (advanced), Excel, Tableau / Power BI / Looker, basic Python or R, statistics fundamentals | Analysts use data that already exists in databases. They don't build the pipelines. Entry-level data role. |
| Data Engineer | Build & maintain the data infrastructure � ETL/ELT pipelines that move data from source systems into data warehouses for analysis. | Python, SQL, Apache Spark, Airflow, Kafka, Snowflake / Redshift / BigQuery, dbt, data modeling | Engineers build the infrastructure that analysts use. More coding-heavy than analyst roles. |
| Analytics Engineer | A newer hybrid role: transform raw data into clean, modeled, trusted datasets using SQL + dbt. Bridge between Data Engineers and Analysts. | SQL (expert), dbt, Snowflake/BigQuery, data modeling, Looker/Tableau, Git | Less pipeline work than Data Engineer, more SQL-focused. Rapidly growing title since 2022. |
| Data Scientist | Use statistics and machine learning to build predictive models � forecasting, recommendation engines, anomaly detection. | Python, R, scikit-learn, TensorFlow/PyTorch, statistics, hypothesis testing, A/B testing, Jupyter notebooks | More research-oriented than ML Engineer. Often has PhD or Master's in quantitative field. |
| ML Engineer | Take machine learning models from research/prototype and deploy them into production systems at scale. | Python, TensorFlow/PyTorch, MLOps (MLflow, Kubeflow), Docker, Kubernetes, AWS SageMaker, model serving | Like Data Scientist but focused on production deployment, not research. More engineering, less statistics. |
| AI Engineer | Build AI-powered applications � chatbots, document processing, content generation, using LLMs and GenAI tools. | Python, LangChain/LlamaIndex, OpenAI/Anthropic APIs, vector databases (Pinecone, Weaviate), RAG architecture, prompt engineering | Newest role (emerged 2023+). Application-focused. Uses pre-trained models rather than training from scratch. |
| BI Developer | Build business intelligence platforms � dashboards, reports, data models optimized for business decision-making. | Tableau, Power BI, Looker, SQL, dimensional modeling (star schema), DAX, data visualization best practices | More business-facing than Data Engineer. Less statistical than Data Scientist. Often reports to business, not engineering. |
Infrastructure, Cloud, DevOps & Security Roles
| Job Title | What They Actually Do | Key Skills on JDs |
|---|---|---|
| DevOps Engineer | Automate the entire build ? test ? deploy pipeline. Write scripts, manage CI/CD tools, configure infrastructure as code. Goal: make deployments faster, safer, and repeatable. | Jenkins/GitHub Actions/GitLab CI, Docker, Kubernetes, Terraform/CloudFormation, Ansible, Python/Bash, AWS/Azure/GCP, Git |
| Cloud Engineer | Design, build, and manage cloud infrastructure � virtual servers, networks, storage, security groups, databases on AWS/Azure/GCP. | AWS (EC2, S3, RDS, Lambda, VPC, IAM) or Azure or GCP equivalents, Terraform, networking (VPC, subnets, security groups), Linux |
| Site Reliability Engineer (SRE) | Keep production systems running reliably. Define SLOs/SLAs, automate incident response, reduce downtime, capacity planning. SRE is an engineering approach to operations. | Python/Go, Kubernetes, Prometheus, Grafana, PagerDuty, SLO/SLA management, incident management, distributed systems |
| Platform Engineer | Build internal developer platforms � tools and infrastructure that make other developers more productive. Newer evolution of DevOps role. | Kubernetes, Backstage (developer portal), Crossplane, GitOps, Terraform, CI/CD, Internal Developer Portals (IDP) |
| Systems Administrator | Manage on-premise or cloud servers � install software, manage user accounts, configure backups, monitor system health. More traditional IT ops role. | Windows Server, Linux (RHEL/Ubuntu), Active Directory, VMware/Hyper-V, PowerShell, Bash, DNS, DHCP |
| Network Engineer | Design and maintain computer networks � routers, switches, firewalls, VPNs, load balancers. Ensure network performance and security. | Cisco (CCNA/CCNP), TCP/IP, DNS, BGP, OSPF, Palo Alto/Fortinet firewalls, SD-WAN, network monitoring (Nagios, SolarWinds) |
| Cybersecurity Analyst | Monitor for threats, investigate security incidents, implement security controls, ensure compliance. "Blue team" (defensive security). | SIEM (Splunk, QRadar, Microsoft Sentinel), firewalls, IDS/IPS, vulnerability scanning (Nessus, Qualys), incident response, CISSP/CEH |
| Security Engineer | Build security into applications and infrastructure � secure coding reviews, penetration testing, identity management, encryption. More hands-on than analyst. | OWASP Top 10, Burp Suite, penetration testing, IAM, encryption, HashiCorp Vault, compliance (SOC2, HIPAA, PCI-DSS) |
Management, Architecture & Non-Coding Roles
| Job Title | What They Do | Key Skills / What to Look For |
|---|---|---|
| Project Manager (PM) | Plan, execute, and deliver projects on time and within budget. Track progress, manage risks, communicate with stakeholders, remove blockers for the team. | PMP certification, CSM, Jira/MS Project, Agile & Waterfall methodologies, budget management, Gantt charts, risk registers, stakeholder management |
| Scrum Master | Facilitate Scrum ceremonies (standups, sprint planning, retrospectives), protect the team from distractions, remove impediments. Note: a Scrum Master is NOT a Project Manager. | CSM/PSM certification (required), deep Agile/Scrum knowledge, coaching skills, conflict resolution. Should NOT be managing tasks or assigning work. |
| Product Manager / Product Owner | Define WHAT to build and WHY (not HOW). Own the product vision and roadmap. Prioritize the backlog. Make trade-off decisions between features. | User research, customer interviews, data analysis, roadmap tools (Aha!, Productboard), stakeholder management, CSPO certification |
| Business Analyst (BA) | Bridge between business stakeholders and technical team. Gather requirements, write documentation, translate business needs into technical specifications. | BRD/FRD documentation, Visio/Lucidchart (process mapping), SQL basics, wire-framing, CBAP certification, domain knowledge |
| Solutions Architect | Design technical solutions that meet business requirements. Evaluate technologies, define system architecture, ensure scalability and security. Senior technical role. | Cloud architecture (AWS/Azure/GCP), system integration, API design, microservices, TOGAF, enterprise architecture patterns. Typically 10+ years experience. |
| Engineering Manager | Manage a team of 5-12 developers. Responsible for hiring, performance reviews, career growth, technical direction, and team productivity. | People management experience + strong technical background. Usually 5+ years as a developer before transitioning to management. |
The Seniority Ladder � What Experience Levels Mean
| Level | Years of Exp | What They Can Do | JD Keywords |
|---|---|---|---|
| Junior / Entry-Level | 0-3 years | Works on well-defined tasks with supervision. Writes code, fixes bugs, learns the codebase. Needs guidance on design decisions. | "Junior," "Associate," "Entry-level," "I/II," "0-3 years" |
| Mid-Level | 3-6 years | Works independently on features. Can design small systems. Participates in code reviews. Starting to mentor juniors. | "Mid," "Developer II/III," "3-5 years," no seniority prefix (just "Software Engineer") |
| Senior | 6-10 years | Leads feature development. Makes architectural decisions. Mentors mid/junior developers. Handles complex technical challenges. | "Senior," "Sr.," "Lead," "6+ years," "owns technical decisions" |
| Staff / Principal | 10-15+ years | Sets technical direction for teams/org. Evaluates new technologies. Cross-team influence. Deep expertise in specific domains. | "Staff," "Principal," "Distinguished," "Fellow," "10+ years," "technical vision" |
| Architect | 10-20+ years | Designs systems at the enterprise level. Technology evaluation. Sets coding standards. Client-facing technical leadership. | "Architect," "Chief Architect," "Enterprise Architect," TOGAF, "system design" |
Mapping Roles to SDLC Phases
The key framework: when you read a JD, place the role on this map instantly.
| SDLC Phase | Primary Roles | Supporting Roles | Key Deliverables |
|---|---|---|---|
| 1. Planning | Project Manager, Program Manager, Product Owner | BA, Architect, CTO, PMO | Project charter, budget, timeline, resource plan |
| 2. Requirements | Business Analyst, Product Manager/Owner | SME, Systems Analyst, UX Researcher | BRD, FRD, user stories, use case diagrams |
| 3. Design | Solutions Architect, Tech Architect, UI/UX Designer | DBA, Security Architect, Lead Dev | HLD, LLD, wireframes, DB schema, API specs |
| 4. Development | Software Engineers (all types), DBAs | Tech Lead, Scrum Master, DevOps | Working code, APIs, unit tests, code reviews |
| 5. Testing | QA Analyst, QA Engineer, SDET | Performance Engineer, BA (UAT) | Test plans, test scripts, bug reports, sign-off |
| 6. Deployment | DevOps Engineer, SRE, Release Manager | Cloud Engineer, DBA, Security | CI/CD pipelines, deployed application, runbooks |
| 7. Maintenance | Support Engineers (L1/L2/L3), SRE | DevOps, DBA, Security Analyst | Patches, incident reports, monitoring dashboards |
Technology Stacks � The Big Picture
A "tech stack" is the combination of languages, frameworks, databases, and tools used to build an application. Knowing stacks helps you match candidates to JDs accurately.
What is a Technology Stack?
Think of a technology stack like the layers of a building. Each layer has a specific purpose, and together they form a complete application:
Frontend (Client Side)
What users see and interact with in their browser or phone. The "face" of the application.
Technologies: HTML, CSS, JavaScript, React, Angular, Vue.js, TypeScript, Tailwind CSS, Next.js, Nuxt.js
Backend (Server Side)
Business logic, data processing, and API layer running on servers. The "brain" of the application.
Technologies: Java/Spring Boot, Python/Django, Node.js/Express, C#/.NET, Go, Ruby on Rails
Database (Data Layer)
Where data is stored, organized, and retrieved. The "memory" of the application.
Technologies: PostgreSQL, MySQL, Oracle, MongoDB, Redis, Cassandra, DynamoDB, Snowflake
Infrastructure & DevOps
Servers, cloud platforms, deployment automation. The "foundation" and "nervous system."
Technologies: AWS/Azure/GCP, Docker, Kubernetes, Terraform, Jenkins, GitHub Actions, Datadog
Common Full-Stack Combinations You Will See
| Stack Name | Frontend | Backend | Database | Where Common |
|---|---|---|---|---|
| MERN | React | Node.js / Express | MongoDB | Startups, JavaScript-heavy companies |
| MEAN | Angular | Node.js / Express | MongoDB | Enterprise JavaScript shops |
| Java Enterprise | Angular or React | Java / Spring Boot | PostgreSQL or Oracle | Banks, insurance, healthcare (most common in US staffing) |
| Python Stack | React or Vue | Python / Django or Flask | PostgreSQL | Data-heavy apps, ML backends, startups |
| .NET Stack | Angular or React | C# / .NET Core | SQL Server or PostgreSQL | Microsoft-ecosystem companies |
| Modern Cloud-Native | React + TypeScript | Go or Node.js | PostgreSQL + Redis | Cloud-native companies, microservices architectures |
Frontend Technologies � Deep Dive
Frontend development builds the user interface � everything a user sees, clicks, and interacts with.
The Big Three Frontend Frameworks
React (by Meta/Facebook)
Market share: ~42% of frontend jobs
What it is: A JavaScript library for building user interfaces using reusable components. Uses JSX � a syntax that lets you write HTML inside JavaScript. Virtual DOM for high performance.
Ecosystem: Next.js (server-side rendering), Redux / Zustand (state management), React Router, React Query (data fetching), React Native (mobile apps using React).
JD signals: "React," "ReactJS," "React.js," "Redux," "hooks," "Next.js," "JSX," "component architecture," "React Native."
Why it dominates: Largest community, most tutorials, most npm packages, backed by Meta. Most new projects choose React.
Angular (by Google)
Market share: ~20% of frontend jobs
What it is: A full opinionated framework (not just a library). TypeScript-first. Comes with built-in routing, forms handling, HTTP client, dependency injection. Steeper learning curve than React.
Ecosystem: RxJS (reactive programming), NgRx (state management), Angular Material (UI components), Angular CLI.
JD signals: "Angular," "Angular 14/15/16/17," "TypeScript," "RxJS," "NgRx," "Angular Material," "Angular CLI."
Where common: Large enterprises, banking, healthcare, government. Companies that value structure and convention.
Vue.js (Community-driven)
Market share: ~10% of frontend jobs
What it is: A progressive framework � easy to learn, flexible, incrementally adoptable. Can be used for simple widgets or full SPAs.
Ecosystem: Nuxt.js (SSR), Pinia/Vuex (state), Vue Router, Vuetify/Quasar (UI frameworks).
JD signals: "Vue," "Vue.js," "Vuex," "Pinia," "Nuxt," "composition API."
Where common: Mid-size companies, agencies, Asian market (very popular in China). Growing in US but still behind React/Angular.
Core Frontend Technologies (Appear on Every JD)
| Technology | What It Is | Why It's on JDs |
|---|---|---|
| HTML5 | Hypertext Markup Language � the structure/skeleton of every web page. Defines headings, paragraphs, images, forms, buttons. | Fundamental. Every frontend developer must know HTML. "HTML5" = current version with features like video, canvas, semantic elements. |
| CSS3 | Cascading Style Sheets � controls visual appearance: colors, fonts, spacing, layout, animations. | Fundamental. Includes modern features: Flexbox, CSS Grid, CSS Variables, animations, media queries for responsive design. |
| JavaScript (ES6+) | The programming language of the web. ES6/ES2015 = modern syntax: arrow functions, async/await, destructuring, modules, classes. | The core language. React/Angular/Vue are all built with JavaScript. "ES6+" means the candidate knows modern syntax (not legacy code). |
| TypeScript | JavaScript with type safety. Adds static types to JavaScript � catches errors at compile time instead of runtime. Created by Microsoft. | Required for Angular. Increasingly standard for React/Vue (65%+ of new projects). JDs that say "TypeScript" expect typed code, not plain JS. |
| Tailwind CSS | A utility-first CSS framework. Instead of writing custom CSS, you apply small utility classes directly in HTML. Very popular since 2021. | Rapidly replacing Bootstrap. "Tailwind" on a JD means the team uses utility-first styling. Candidate should know responsive design with Tailwind. |
| Webpack / Vite | Build tools that bundle JavaScript, CSS, images into optimized files for production. Webpack = older standard. Vite = newer, faster alternative. | "Webpack" = established. "Vite" = modern. Both handle module bundling, code splitting, hot module replacement during development. |
| Git | Version control system. Tracks all code changes. Developers work on branches, create pull requests, review code, merge changes. | Every developer must know Git. Platforms: GitHub (most popular), GitLab, Bitbucket. "Git workflow" = branching strategy (GitFlow, trunk-based). |
Backend Technologies & Databases
Backend development powers the server-side logic. Backend roles account for the largest share of IT JDs in US staffing.
Backend Languages & Frameworks
| Language | Primary Framework | Where Used | JD Keywords |
|---|---|---|---|
| Java | Spring Boot, Spring MVC, Hibernate (ORM) | Enterprise (banking, insurance, healthcare, Fortune 500). #1 most requested backend language in US staffing. | "Java 8/11/17/21," "Spring Boot," "microservices," "Maven/Gradle," "JPA/Hibernate," "REST APIs," "Kafka" |
| Python | Django, Flask, FastAPI | Data-heavy applications, ML backends, startups, automation, web apps. #2 most requested. | "Python 3.x," "Django REST Framework," "Flask," "FastAPI," "Celery," "pandas," "SQLAlchemy" |
| C# / .NET | .NET Core, ASP.NET, Entity Framework | Microsoft ecosystem companies, Windows-based enterprises, gaming (Unity), financial services. | "C#," ".NET Core 6/7/8," "ASP.NET Web API," "Entity Framework," "Azure," "LINQ," "Blazor" |
| Node.js | Express.js, NestJS, Fastify | Startups, JavaScript-heavy companies, real-time apps (chat, streaming), BFF (backend for frontend). | "Node.js," "Express," "NestJS," "npm/yarn," "async/await," "WebSocket," "event-driven" |
| Go (Golang) | Gin, Echo, standard library | Cloud-native companies (Google, Uber, Docker), microservices, high-performance systems, DevOps tools. | "Go/Golang," "goroutines," "channels," "gRPC," "high concurrency," "microservices" |
| Ruby | Ruby on Rails | Startups, web apps, e-commerce (Shopify, early GitHub, early Twitter). Declining demand since 2020. | "Ruby on Rails," "ActiveRecord," "RSpec," "Sidekiq." Note: fewer new projects choose Ruby. |
Databases � Relational vs. NoSQL
Every application stores data in a database. Understanding the two major categories is essential for matching candidates to JDs:
Relational (SQL) Databases
Structure: Data stored in tables with rows and columns, like a spreadsheet. Tables are related to each other through keys (e.g., a User table linked to an Orders table).
Query language: SQL (Structured Query Language) � a standardized language for querying and manipulating data.
Strengths: Data integrity, ACID compliance (transactions are reliable), complex queries, mature tooling.
Best for: Applications where data structure is well-defined and relationships are important � banking, e-commerce, ERP, CRM.
Examples: PostgreSQL, MySQL, Oracle, SQL Server, MariaDB.
NoSQL Databases
Structure: Flexible schema � data can be stored as documents (JSON), key-value pairs, wide columns, or graphs. No predefined table structure.
Query language: Varies by database � MongoDB uses MQL, Cassandra uses CQL, Redis uses commands.
Strengths: Flexibility, horizontal scaling, high performance for specific use cases, handles unstructured data well.
Best for: Applications with evolving schemas, massive scale, real-time data, IoT, content management, caching.
Examples: MongoDB (documents), Redis (key-value/caching), Cassandra (wide-column), DynamoDB (key-value), Neo4j (graph).
Database-Specific Details for JD Matching
| Database | Type | When Used | JD Keywords |
|---|---|---|---|
| PostgreSQL | Relational | Most modern applications. Open-source, powerful, supports JSON. Default choice for startups and cloud-native apps. | "PostgreSQL," "Postgres," "PL/pgSQL," "JSONB," "indexing," "partitioning," "PostGIS" |
| MySQL | Relational | Web applications, WordPress, e-commerce, LAMP stack. Very common in small-to-mid-size applications. | "MySQL," "InnoDB," "replication," "sharding," "MySQL Workbench" |
| Oracle | Relational | Large enterprises, banking, healthcare. Expensive licensing. Legacy systems. Often requires 10+ years experience. | "Oracle," "PL/SQL," "RAC," "Data Guard," "RMAN," "Oracle Cloud," "Exadata" |
| SQL Server | Relational | Microsoft ecosystem, .NET applications, BI/reporting (SSIS/SSRS/SSAS). | "SQL Server," "T-SQL," "SSIS/SSRS/SSAS," "Azure SQL," "Always On," "stored procedures" |
| MongoDB | NoSQL (Document) | Flexible schema apps, content management, IoT, real-time analytics, mobile backends. | "MongoDB," "Mongoose," "aggregation pipeline," "MongoDB Atlas," "document model," "BSON" |
| Redis | NoSQL (Key-Value) | Caching layer (most common use), session storage, real-time leaderboards, rate limiting, message queues. | "Redis," "caching," "in-memory," "pub/sub," "cache invalidation," "Redis Cluster" |
| Snowflake / Redshift / BigQuery | Cloud Data Warehouse | Analytics and BI workloads. Store massive datasets for reporting. Used by Data Engineers and Analysts. | "Snowflake," "Redshift," "BigQuery," "data warehouse," "ELT," "dbt," "dimensional modeling" |
Cloud Platforms & DevOps
Cloud computing and DevOps are the fastest-growing areas in IT hiring. These roles command premium rates.
The Big 3 Cloud Providers
AWS (Amazon Web Services)
Market share: ~32% (dominant leader).
Core services: EC2 (virtual servers), S3 (object storage), RDS (managed databases), Lambda (serverless functions), ECS/EKS (container management), VPC (networking), IAM (access control), CloudFormation (IaC), SQS/SNS (messaging).
Certifications: AWS Solutions Architect (most common on JDs), AWS Developer, AWS SysOps Administrator, AWS DevOps Engineer Professional.
JD signal: "AWS," specific service names (EC2, S3, Lambda, RDS), "cloud-native," "serverless," "AWS certified."
Microsoft Azure
Market share: ~23% (#2).
Core services: Azure VMs, Azure SQL Database, Azure Functions, AKS (Kubernetes), Azure DevOps, Azure Active Directory, Blob Storage, Azure Monitor.
Certifications: AZ-104 (Admin), AZ-204 (Developer), AZ-305 (Solutions Architect), AZ-400 (DevOps), AZ-900 (Fundamentals).
JD signal: "Azure," "Azure DevOps," ".NET + Azure," "hybrid cloud," "Microsoft 365 integration," "Azure AD."
Note: Dominant in enterprises already using Microsoft stack (.NET, Office 365, Teams, Active Directory).
Google Cloud (GCP)
Market share: ~11% (#3).
Core services: Compute Engine, Cloud Storage, BigQuery (analytics powerhouse), Cloud Run, GKE (Kubernetes � Google invented K8s), Vertex AI, Cloud Functions, Pub/Sub.
Certifications: Associate Cloud Engineer, Professional Cloud Architect, Professional Data Engineer.
JD signal: "GCP," "BigQuery," "Vertex AI," "GKE," "Cloud Run."
Note: Strong in data/ML workloads. BigQuery is the most popular cloud data warehouse.
The DevOps Toolchain
DevOps is a practice, not a single tool. DevOps JDs mention a combination of tools from these categories:
| Category | What It Does | Key Tools |
|---|---|---|
| Version Control | Track code changes, branching, merging | Git, GitHub, GitLab, Bitbucket |
| CI/CD Pipelines | Automate build ? test ? deploy | Jenkins (most common), GitHub Actions, GitLab CI, CircleCI, Azure DevOps Pipelines, ArgoCD |
| Containerization | Package apps in portable containers | Docker (create containers), Kubernetes/K8s (orchestrate containers at scale), Helm (K8s package manager) |
| Infrastructure as Code | Define infrastructure in code files | Terraform (multi-cloud, most popular), CloudFormation (AWS only), Pulumi, Crossplane |
| Configuration Mgmt | Automate server setup & configuration | Ansible (agentless, most popular), Chef, Puppet, SaltStack |
| Monitoring & Observability | Track application health & performance | Datadog, Prometheus + Grafana, New Relic, Splunk, ELK Stack (Elasticsearch + Logstash + Kibana) |
| Incident Management | Alert on-call engineers when things break | PagerDuty, OpsGenie, VictorOps, ServiceNow |
| Scripting | Automate repetitive tasks | Bash (Linux), Python, PowerShell (Windows) |
QA & Testing Domain
QA roles account for ~15-20% of IT staffing requisitions. Know the three QA career tracks inside out.
Three QA Career Tracks
Manual QA Analyst
What they do: Execute test cases by hand � clicking through the application, following test scripts, verifying features work as expected. Document bugs in Jira. Write test plans from requirements.
Skills: Test case writing, bug tracking (Jira), SQL (for data validation), domain knowledge, attention to detail, communication.
Entry barrier: Lowest � good entry point into IT for non-coders.
Rate range: $30-55/hr W2.
QA Automation Engineer
What they do: Write automated test scripts that run without human intervention. Build test frameworks. Integrate tests into CI/CD pipelines so tests run automatically on every code change.
Skills: Selenium, Cypress, or Playwright (browser automation), Java or Python (scripting), TestNG/JUnit, REST Assured (API testing), CI/CD, Git.
Entry barrier: Medium � requires programming skills.
Rate range: $50-90/hr W2.
SDET (Software Dev Engineer in Test)
What they do: A developer who specializes in testing. Builds entire test infrastructure from scratch � custom frameworks, testing tools, performance test suites. Writes production-quality code.
Skills: Strong coding (Java/Python/JS), framework architecture, API testing, performance testing (JMeter/Gatling), Docker, CI/CD, system design.
Entry barrier: High � essentially a developer role.
Rate range: $65-110/hr W2.
Testing Tools Reference
| Tool | What It Does | Used By |
|---|---|---|
| Selenium | Browser automation � simulates user clicks, form fills, navigation. The oldest and most widely used automation tool. | QA Automation Engineers. Most common on JDs. Open-source. |
| Cypress | Modern browser testing � faster than Selenium, easier setup, better debugging. JavaScript-only. Growing rapidly. | Frontend-heavy QA teams. JDs increasingly list Cypress alongside or instead of Selenium. |
| Playwright | Microsoft's browser automation tool. Supports multiple languages (JS, Python, Java, C#). Cross-browser. Newest of the three. | Modern QA teams, especially Microsoft-stack companies. Growing fast. |
| Postman | API testing � send HTTP requests, validate responses, create test collections. Used for manual and automated API testing. | All QA roles + backend developers. Almost universal for API testing. |
| JMeter | Performance/load testing � simulate thousands of concurrent users to test application performance under stress. | Performance Engineers, Senior QA. Open-source. |
| Appium | Mobile app testing � automate tests for iOS and Android applications. Similar concept to Selenium but for mobile. | Mobile QA Engineers. Required when JD involves mobile application testing. |
Emerging Technologies & Niche Domains
Cutting-edge areas appearing on JDs in 2025-2026. Recruiters who understand these source for roles before competitors.
AI / GenAI Engineering
Building AI-powered applications using Large Language Models (LLMs), RAG (Retrieval Augmented Generation), vector databases, and AI orchestration frameworks.
Skills: Python, LangChain/LlamaIndex, OpenAI/Anthropic/Google APIs, vector databases (Pinecone, Weaviate, ChromaDB), prompt engineering, fine-tuning, RAG architecture, MLOps.
Rate premium: 20-40% above standard backend rates. Very high demand, limited supply.
Platform Engineering
Building Internal Developer Platforms (IDPs) � tools that help developers be more productive. Evolution of DevOps focused on developer experience.
Skills: Kubernetes, Backstage (Spotify's developer portal), Crossplane, GitOps, Terraform, service mesh (Istio, Linkerd), golden paths.
Rate: $70-130/hr W2. Extremely hard to fill. Title emerging since 2023.
Data / Analytics Engineering
The modern data stack � building data pipelines using dbt, Snowflake, Databricks, Fivetran, and Airflow. Analytics Engineering is the hottest data role.
Skills: SQL (expert), dbt, Snowflake/BigQuery/Databricks, Python, Spark, Kafka, Airflow, data modeling, ELT patterns.
Distinction: Analytics Engineer = SQL + dbt + BI. Data Engineer = Python + Spark + pipelines. Different JDs.
Cybersecurity / Zero Trust
Growing demand driven by ransomware, data breaches, and compliance requirements. Zero Trust architecture = "never trust, always verify."
Skills: SIEM, EDR, SOAR, identity management (Okta, Azure AD), cloud security (CSPM, CWPP), compliance (SOC2, HIPAA, FedRAMP).
Rate: $65-130/hr W2. Security clearance adds 20-30% premium.
JD Breakdown � The Elimination Method
The single most important skill for an IT recruiter: systematically analyzing any Job Description to extract actionable sourcing intelligence.
The 6-Step JD Breakdown Method
Apply this method to every single IT JD you receive. With practice, it takes 3-5 minutes per JD.
Step 1: Identify Role Category
Is this Development, QA, DevOps, Data, Cloud, Security, or Management? This determines your sourcing strategy, job boards, and candidate pool.
Step 2: Extract Must-Haves
Keywords: "required," "must have," "X+ years of." These are non-negotiable. Usually 3-5 core skills. Candidates missing ANY must-have are disqualified.
Step 3: Extract Nice-to-Haves
Keywords: "preferred," "bonus," "plus," "experience with X is a plus." These differentiate good candidates from great ones. Having 2+ nice-to-haves strengthens submission.
Step 4: Map Experience Level
Junior (0-3), Mid (3-6), Senior (6-10), Staff/Principal (10+). Match to seniority ladder. A "5+ years" JD is mid-to-senior. A "10+ years" JD is Staff+.
Step 5: Identify Deal-Breakers
Visa restrictions, location (onsite/hybrid/remote), certifications (AWS SA, PMP), security clearance, specific degree, no C2C. These eliminate before skills.
Step 6: Build Boolean String
Convert must-have skills into Boolean search. Use AND for required, OR for alternatives, quotes for exact phrases, parentheses for grouping. Test on LinkedIn.
Live Example: Breaking Down a Real JD
| Step | Analysis |
|---|---|
| 1. Category | Backend Development. SDLC Phase 4. |
| 2. Must-Haves | Java (7+ yrs), Spring Boot, Microservices, REST APIs, PostgreSQL, Kafka, Docker/Kubernetes, CI/CD, Agile |
| 3. Nice-to-Haves | AWS (ECS, Lambda, RDS), React, GraphQL, HIPAA compliance |
| 4. Experience Level | Senior (7+ years). Map to Senior-Staff tier. |
| 5. Deal-Breakers | US Citizen/GC only (no visa candidates). No C2C. Remote but US-based only. Healthcare = HIPAA awareness needed. |
| 6. Boolean String | See below |
Boolean Sourcing for IT Roles
Boolean search is the language of recruitment sourcing. Master these operators and templates to find candidates faster than your competition.
The 5 Boolean Operators
| Operator | What It Does | Example | Result |
|---|---|---|---|
| AND | Both terms must be present | "Java" AND "Spring Boot" | Only profiles with BOTH Java and Spring Boot |
| OR | Either term can be present | "React" OR "Angular" OR "Vue" | Profiles with at least ONE of these frameworks |
| NOT | Exclude a term | "Java" NOT "JavaScript" | Java developers, excluding those who only know JavaScript |
| "Quotes" | Exact phrase match | "machine learning" | Finds the exact phrase, not "machine" and "learning" separately |
| ( ) Parentheses | Group terms together | ("Python" OR "Java") AND "AWS" | Python or Java developers who also know AWS |
Boolean String Templates � Copy & Customize
Java Backend Developer
React Frontend Developer
DevOps Engineer
Data Engineer
QA Automation Engineer
AI / GenAI Engineer
Candidate Vetting for IT Roles
Technical screening questions, red flags to catch, visa compliance checks, and resume authenticity verification.
Screening Call � Questions to Ask
| Question | What to Listen For | Red Flag |
|---|---|---|
| "Walk me through your current project � what does your team build and what tech stack do you use?" | Specific technology names, architecture details (microservices, monolith), team size, their specific role vs. team role. | Vague answers, can't name specific tools, describes only high-level concepts without implementation details. |
| "What version of [Java/React/Python/.NET] are you working with?" | Current versions: Java 17/21, React 18+, Python 3.11+, .NET 8. Shows they're on modern projects. | Only knows Java 8 (released 2014), only React class components (pre-2019 pattern), Python 2.x (end of life). |
| "How do you deploy your code to production?" | "We use Jenkins/GitHub Actions to trigger builds, Docker containers, deploy to Kubernetes on AWS." Shows CI/CD awareness. | "I commit code and someone else deploys it" or "We manually copy files to the server." Indicates legacy environment. |
| "Do you work in Agile? What's your sprint length?" | Genuine: "2-week sprints, daily standups at 9am, we use Jira for tracking." Shows real Agile experience. | Can't explain what a sprint is, doesn't know Scrum ceremonies, says "we just get assigned tasks." |
| "Tell me about a challenging bug you recently solved." | Structured problem-solving: what was the issue, how did they debug it, what tools they used, what was the fix. | Can't recall any specific example. Gives only theoretical answers without real-world details. |
| "What's the difference between [related technologies]?" (e.g., SQL vs NoSQL, Docker vs Kubernetes, REST vs GraphQL) | Clear, accurate explanation showing genuine understanding of trade-offs and when to use each. | Confuses the concepts, gives textbook definition without practical understanding. |
Resume Red Flags � Catch Before Submission
- Technology timeline mismatch: Claims 10 years of React (launched 2013, widely adopted 2016), 8 years of Kubernetes (launched 2014, mainstream 2017), 5 years of LangChain (launched 2022).
- Resume lists 20+ technologies: No one is expert in everything. Genuine resumes show depth in 5-8 core technologies, not breadth across 20+.
- Different person on phone vs. interview: If the voice, accent, or technical depth doesn't match between your screening call and the client interview, this is proxy/substitution fraud.
- Can't discuss their own resume: If a candidate can't explain a project listed on their resume in detail, the resume was likely fabricated.
- Generic Gmail/Yahoo email for an employed professional: While not always a red flag, combined with other signals it suggests the "employer" on the resume may not be real.
- Identical resumes from same vendor: If you receive two resumes with identical formatting, similar project descriptions, and both from the same small consulting company, investigate.
Visa & Work Authorization Compliance
| Status | Work Authorization | Restrictions | What to Ask |
|---|---|---|---|
| US Citizen | Full � no restrictions | None | No further questions needed |
| Green Card (Permanent Resident) | Full � no restrictions | None (functionally same as citizen for employment) | No further questions needed |
| H1B Visa | Employer-specific | Tied to sponsoring employer. Transfer required for new job. 3+3 year validity (max 6 years). Can be extended if green card in process. | "Who is your current H1B sponsor? Are you open to transfer? Is your green card process started?" |
| H4 EAD | Dependent of H1B holder | Valid only while H1B spouse's visa and GC process is active. Can be revoked by policy changes. | "When does your EAD expire? Is your spouse's green card in process?" |
| OPT (F1 Student) | Temporary (12 months, or 36 months for STEM) | Time-limited. Must be related to field of study. STEM OPT requires E-Verify employer. | "When does your OPT expire? Is this STEM OPT? Are you looking for H1B sponsorship?" |
| L1 Visa | Intra-company transfer | Tied to the company that transferred the employee. Cannot work for different employer. | Rarely available for staffing � candidate must work for their sponsoring company. |
| TN Visa (USMCA) | Canadian/Mexican citizens | Specific professional categories. Renewable indefinitely. No green card intent allowed (technically). | "Are you a Canadian/Mexican citizen on TN status?" |
Pay Rates & Bill Rates � US Market
Current market rate benchmarks, engagement types (W2/1099/C2C), and rate negotiation guidance.
IT Pay Rate Benchmarks � 2025/2026 US Market (W2 Hourly)
| Role | Junior (0-3yr) | Mid (3-6yr) | Senior (6-10yr) | Lead/Staff (10+yr) |
|---|---|---|---|---|
| Java Developer | $35-50 | $50-70 | $70-95 | $95-120 |
| React/Frontend Dev | $30-45 | $45-65 | $65-90 | $90-115 |
| Python Developer | $35-50 | $50-70 | $70-95 | $95-120 |
| .NET Developer | $30-45 | $45-65 | $65-85 | $85-110 |
| Full Stack Developer | $35-50 | $50-70 | $70-95 | $95-120 |
| DevOps Engineer | $40-55 | $55-75 | $75-100 | $100-130 |
| Cloud Architect | N/A | $65-85 | $85-120 | $120-160 |
| Data Engineer | $40-55 | $55-75 | $75-100 | $100-130 |
| Data Scientist | $40-55 | $55-80 | $80-110 | $110-140 |
| QA Manual | $25-35 | $35-45 | $45-55 | $55-65 |
| QA Automation / SDET | $35-50 | $50-70 | $70-90 | $90-110 |
| Cybersecurity | $35-50 | $50-70 | $70-95 | $95-130 |
| AI/ML Engineer | $45-60 | $60-85 | $85-120 | $120-160 |
| Business Analyst | $30-40 | $40-55 | $55-75 | $75-95 |
| Project Manager | $35-45 | $45-65 | $65-90 | $90-120 |
| Scrum Master | N/A | $45-60 | $60-85 | $85-105 |
Engagement Types: W2 vs. 1099 vs. C2C
W2 (Employee)
Employer handles payroll taxes (FICA 7.65%), may provide benefits. Candidate receives paycheck with taxes withheld.
Total employer burden: ~25-35% above hourly rate.
Example: $80/hr W2 costs employer ~$100-108/hr fully loaded.
Who uses it: Most enterprise clients prefer W2 for compliance reasons.
1099 (Independent Contractor)
Contractor handles own taxes, insurance, benefits. No payroll burden on employer.
Typical rate: 15-20% higher than W2 equivalent to compensate for self-employment tax (15.3%).
Conversion: W2 rate � 1.15-1.20 � 1099 rate.
Risk: IRS misclassification. Contractor must control their own schedule, tools, and methods.
C2C (Corp-to-Corp)
Candidate works through their own LLC or another vendor company. No payroll burden on client.
Typical rate: Highest � intermediary company takes margin.
Conversion: W2 rate � 1.25-1.35 � C2C rate.
Note: Many clients do NOT accept C2C. Common for H1B visa holders through their sponsoring employer.
Real JD Scenarios � Practice Exercises
Apply the 6-Step Breakdown Method to these realistic JDs. Work through each independently before checking the analysis.
Analysis:
Category: Full Stack (Frontend + Backend). SDLC Phase 4.
Must-Haves: React, TypeScript, Node.js, PostgreSQL, AWS, Git, Agile. This is a MERN-style stack on AWS.
Nice-to-Haves: GraphQL, Docker, Redis, WebSocket. These indicate real-time features and modern architecture.
Level: Mid (4-6 years). Not junior, not senior.
Deal-Breakers: NYC hybrid (must be in commuting distance). US persons only � SEC compliance may require citizenship specifically. Confirm with client whether Green Card qualifies.
Rate: $60-70/hr W2 for mid-level in NYC is competitive but tight. NYC premium usually pushes rates higher.
Sourcing: LinkedIn Boolean for React + Node.js + AWS in NYC metro. Also check AngelList/Wellfound (startup talent pool).
Analysis:
Category: DevOps/Cloud. SDLC Phase 6 (Deployment) + Phase 7 (Maintenance).
Must-Haves: AWS (multiple services), Docker, Kubernetes, Terraform, Jenkins, Python/Bash, Linux, monitoring, HIPAA.
Level: Senior (8+ years) � extensive hands-on, not just certifications.
Deal-Breakers: HIPAA compliance is healthcare-specific (candidate must understand PHI, audit logging, encryption at rest/transit). No C2C narrows pool. Secret clearance preferred = government healthcare (VA, military hospitals). Clearance candidates command premium.
Rate: $90-105/hr W2 for senior DevOps with HIPAA + clearance is at market. Could negotiate up to $110 for right candidate with active clearance.
Analysis:
Category: Data Engineering. Spans SDLC Phase 4 (building pipelines) and Phase 7 (maintaining data systems).
Must-Haves: Python, SQL, Spark, Snowflake, Airflow, dbt, Kafka, data modeling � this is the complete "modern data stack."
Level: Senior (6+ years). Must have hands-on pipeline building, not just SQL queries.
Deal-Breakers: None significant � open to all work authorizations is inclusive. Remote is flexible.
Rate: $80-95/hr is slightly below market for this skill combination. Candidate pool may be limited � Spark + Snowflake + Airflow + dbt together is a premium combination.
Key Distinction: This is a Data ENGINEER role (builds pipelines), not a Data ANALYST role (queries data). Don't submit candidates whose primary skill is Tableau/Power BI.
Analysis:
Category: QA Automation. SDLC Phase 5 (Testing).
Must-Haves: Selenium + Java + TestNG (classic automation stack), REST Assured (API testing), Jenkins (CI/CD), SQL.
Level: Mid-Senior (5+ years). Should have built automation frameworks, not just written scripts.
Deal-Breakers: Onsite Dallas (relocation or local only). US Citizen/GC only. Banking = background check with credit check. Banking domain experience is a strong plus.
Rate: $55-65/hr for QA Automation in Dallas is reasonable. Banking adds compliance overhead but not usually rate premium.
Screening tip: Ask "Have you built an automation framework from scratch, or did you add tests to an existing one?" Senior QA should be able to architect frameworks.
Glossary � IT Terms A to Z
Quick-reference definitions for every technical term you will encounter in IT JDs and conversations.
| Term | Definition |
|---|---|
| Agile | An iterative approach to software development where work is delivered in small increments (sprints) rather than all at once. |
| API (Application Programming Interface) | A set of rules that allows different software applications to communicate with each other. REST APIs and GraphQL are the two main types. |
| AWS (Amazon Web Services) | Amazon's cloud computing platform � the market leader. Provides servers, databases, storage, and 200+ services on demand. |
| Backend | The server-side of an application � business logic, databases, APIs. Users don't see it directly, but it powers everything. |
| Boolean Search | A search method using operators (AND, OR, NOT, quotes, parentheses) to create precise queries for finding candidates. |
| C2C (Corp-to-Corp) | An engagement type where the candidate works through their own company or another vendor. Highest rates, least common acceptance. |
| CI/CD | Continuous Integration / Continuous Delivery � automated pipelines that build, test, and deploy code whenever developers make changes. |
| Cloud Computing | Renting computing resources (servers, storage, databases) from providers like AWS, Azure, GCP instead of owning physical hardware. |
| Container / Docker | A lightweight, portable package containing an application and all its dependencies. Docker creates containers; Kubernetes manages them at scale. |
| DevOps | A culture and set of practices that automates and integrates software development (Dev) and IT operations (Ops). |
| ELT/ETL | Extract, Load, Transform (or Extract, Transform, Load) � processes for moving data from source systems into data warehouses. |
| Frontend | The client-side of an application � everything users see and interact with in their browser or mobile device. |
| Full Stack | A developer who works on both frontend and backend � end-to-end feature development. |
| Git | A version control system that tracks code changes. Used by virtually every developer. GitHub/GitLab/Bitbucket host Git repositories. |
| GraphQL | An API query language (alternative to REST) that lets clients request exactly the data they need. Created by Facebook. |
| HIPAA | Health Insurance Portability and Accountability Act � US law that protects patient health information (PHI). Healthcare IT JDs often require HIPAA compliance experience. |
| IaC (Infrastructure as Code) | Defining cloud infrastructure (servers, networks, databases) in code files (Terraform, CloudFormation) rather than manual configuration. |
| Kafka | Apache Kafka � a distributed event streaming platform used for real-time data pipelines and messaging between microservices. |
| Kubernetes (K8s) | An open-source container orchestration platform. Manages deployment, scaling, and networking of Docker containers. Created by Google. |
| LLM (Large Language Model) | AI models trained on massive text data that can generate human-like text. Examples: GPT-4, Claude, Gemini. Powers the GenAI engineering boom. |
| Microservices | An architecture where an application is built as a collection of small, independent services (vs. a single "monolith"). Each service does one thing well. |
| MLOps | Machine Learning Operations � DevOps practices applied to ML model lifecycle: training, deploying, monitoring, retraining ML models in production. |
| NoSQL | Non-relational databases (MongoDB, Redis, Cassandra, DynamoDB) that offer flexible schemas, horizontal scaling, and specialized data models. |
| OPT (Optional Practical Training) | Temporary work authorization for F1 student visa holders. 12 months standard, 36 months for STEM fields. |
| RAG (Retrieval Augmented Generation) | An AI architecture pattern that combines LLMs with external knowledge bases. The LLM retrieves relevant documents before generating answers. |
| REST API | Representational State Transfer � the most common API design style. Uses HTTP methods (GET, POST, PUT, DELETE) to interact with resources. |
| SDLC | Software Development Life Cycle � the structured process for building software: Planning ? Requirements ? Design ? Development ? Testing ? Deployment ? Maintenance. |
| SDET | Software Development Engineer in Test � a developer who specializes in building test automation frameworks and testing infrastructure. |
| Sprint | A fixed time period (usually 2 weeks) in Agile/Scrum where a set of features is planned, built, tested, and delivered. |
| SRE (Site Reliability Engineering) | An engineering discipline focused on keeping production systems reliable, available, and performant. Combines software engineering with operations. |
| SQL | Structured Query Language � the standard language for querying and manipulating relational databases. Every IT professional should know basic SQL. |
| Tech Stack | The combination of programming languages, frameworks, databases, and tools used to build an application. Example: React + Node.js + PostgreSQL + AWS. |
| Terraform | An Infrastructure as Code tool by HashiCorp. Defines cloud resources in configuration files. Multi-cloud (works with AWS, Azure, GCP). |
| TypeScript | A superset of JavaScript that adds static types. Catches bugs at compile time. Required for Angular, increasingly standard for React/Vue. |
| UAT (User Acceptance Testing) | The final testing phase where actual business users verify the software meets their requirements before go-live. |
| W2 | Employment engagement type where the employer handles payroll taxes and the candidate is an employee (full-time or contract). Most common in US staffing. |