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