•••• is serving as a trusted IT Outsourcing partner in line with the needs of World's most prestigious firms and carried out successful projects worldwide.

Responsibilities:

  • Design, build, and maintain automated testing frameworks tailored for enterprise cloud data platforms (GCP, Databricks).

  • Formulate data validation strategies and automate the generation of tamper-evident test documentation required for regulatory compliance.

  • Implement automated data quality checks, schema validations, reconciliation pipelines, and data integrity verification (ALCOA+ principles).

  • Partner with compliance and quality teams to maintain continuous audit readiness and produce formal Computerized System Validation (CSV/CSA) deliverables.

  • Automate regression, integration, and end-to-end data pipeline tests across complex ETL/ELT workflows.

  • Embed automated test suites and validation gates into CI/CD pipelines alongside data engineering and platform teams.

Skills:

  • 6–9 years of professional experience in data quality assurance, test automation, or data platform engineering.

  • Deep expertise in building test automation frameworks for distributed cloud and data platforms (using Python, pytest, Great Expectations, Soda, or custom test harnesses).

  • Advanced proficiency in Python and SQL for complex data reconciliation, test scripting, and data transformations.

  • Proven background in designing automated data quality, reconciliation, and integrity checks across large-scale data sets.

  • Solid understanding of validation practices in regulated sectors, with strong preference for GxP (pharmaceutical, life sciences, healthcare, or medical devices) and CSV/CSA workflows.

  • Hands-on experience implementing automated test evidence collection, audit trail verification, and compliance reporting.

  • Practical experience with Git, CI/CD pipelines (GitLab CI, GitHub Actions), and containerized/cloud test runners.

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