ETL Testing (2051)

SDET — Key Skills & Requirements

Software Development Engineer in Test • 8 Years Experience

Profile v1 — Data & ETL Focus

Primary Skills

ETL & Data Pipeline Testing

ETL Workflows • Data Pipelines • Data Validation

• ETL Testing: Validates data accuracy across extraction transformation and load.

• Pipeline Integrity: Implement automated checks to monitor pipeline health performance and error handling.

• Data Validation: Ensures schema type and business-rule conformance including data validation and reconciliation between source and target systems

• Databases : Knowledge of relational and non-relational databases with likes of MySQL PostgreSQL MongoDB DynamoDB

Languages & Frameworks

JavaScript • Python • Pytest

• Core Languages: Proficient in JavaScript or Python for automation

• Test Frameworks: Hands-on with frameworks as Pytest or equivalent

• Framework Design: Build scale and maintain automation frameworks end-to-end

Cloud Infrastructure & CI/CD

AWS • SQL • CI/CD Pipelines

• Cloud Exposure: Working knowledge of AWS/Azure services for test environments

• SQL Proficiency: Uses SQL to query validate and debug data confidently

• CI/CD Integration: Integrates test suites into Jenkins GitHub Actions GitLab CI etc.

Secondary Skills

UI & API Testing

UI Automation • REST APIs • Contract Testing • Playwright

• UI Automation: End-to-end browser testing across modern web applications with frameworks as Cypress Playwright

• API Testing: Validates REST/GraphQL APIs for correctness and edge cases

• Cross-layer Coverage: Bridges UI and API layers for integrated test coverage

• Tooling: Experience with tools like Postman/Insomnia/Newman

Debugging & Distributed Systems

Microservices • Root Cause Analysis

• Root Cause Analysis: Strong diagnostic skills for complex multi-system issues tracing failures across services logs and data layers

• Distributed Debugging: Exposure to Power BI Splunk/Grafana or other monitoring/reporting tools.

Good to Have

AI-Driven Testing

AI-Testing • Agentic AI

• AI Testing: Experience with testing AI powered solutions.

• Agentic AI: Experience with Agentic based solutions like MCP RAG Prompting including testing & developing similar solutions.

Domain Knowledge and Test Management

Domain • Test Management

• Domain: Candidates with previous experience/knowledge of Pharma industries would be preferred.

• Test Management: Experience with tools like Jira ALM TestRail along with project methodologies such as Agile Kanban.

Experience Requirement: 8 years — preferably in an SDET or QA Engineering role