Description:

Capgemini is hiring an experienced ETL & Python Testing Engineer to join its global Quality Engineering & Testing division across multiple major Indian hubs. In this data-intensive quality engineering role, you will design, develop, and scale automated validation frameworks to test complex, high-concurrency data pipelines. Your day-to-day work moves beyond standard UI automation to focus on backend data integrity—performing deep ETL transformations, checking schema logic, running validation queries via SQL automation, and executing end-to-end data processing scripts in Unix/Linux ecosystems. You will own the integration of these automated suites into CI/CD pipelines to ensure seamless, continuous regression tracking.

Key Technical Skills:

Python, Robot Framework, ETL Testing, Data Pipeline Validation, SQL Automation, Unix/Linux Shell, CI/CD, Jenkins, Git, GitHub Actions, UrbanCode Deploy (UCD), JIRA, qTest, Data Quality Auditing

Requirements:

• 4+ years of professional experience in Python development, test automation scripting, and backend data-driven validation.
• Deep programming proficiency in Python combined with hands-on experience building and maintaining robust test blocks using the Robot Framework.
• Proven expertise in ETL testing, including systematic data extraction checks, transformational business logic mapping, source-to-target data matching, and end-to-end workflow verification.
• Strong operational experience executing and managing automated jobs within Unix/Linux environments, backed by advanced SQL querying skills for data quality, reporting, and schema verification.
• Active experience configuring and monitoring automated regression jobs within CI/CD pipelines using tools like Jenkins, Git, GitHub Actions, Helios, or UrbanCode Deploy (UCD).
• Thorough command over standard QA/QE methodologies, agile frameworks, defect tracking inside JIRA, and test-case version control utilizing qTest or Confluence.
• Foundational analytical awareness of business intelligence (BI) concepts, statistics, data processing models, or basic data science principles.