Job Requirements

Role Overview: Lead the modernization and transformation of ETL and data testing across AZ projects by assessing existing data testing processes, identifying automation, standardization and reuse opportunities, and implementing scalable solutions that reduce repetitive effort and deliver measurable productivity and cost efficiencies.

Key Responsibilities: Analyse ETL, DBT, Snowflake and BI testing projects to identify opportunities for automation, standardization, consolidation and reuse. Modernize legacy data testing pipelines and design scalable automated frameworks for high-volume ETL, DBT, data pipelines and BI/report validation. Identify repetitive testing activities and develop reusable frameworks, components and accelerators to eliminate duplicated effort across projects.

Establish common data validation patterns and reusable test assets across the portfolio. Integrate data quality checkpoints and automated validation into CI/CD and DevOps workflows. Drive automation of data reconciliation, transformation validation, data quality and regression testing.

Identify opportunities to improve testing productivity, reduce manual effort and optimize FTE requirements across ETL/data projects. Partner with engineering,



DevOps and testing teams to implement and scale data testing solutions. Evaluate and adopt emerging technologies and AI-enabled capabilities to enhance data testing and automation.

Provide technical guidance and mentoring to data/ETL testing teams and establish best practices. Track and demonstrate automation coverage, productivity gains, reuse and cost-efficiency improvements.

Required Skills &

Experience: 10–12 years of experience in Data Engineering, Data Testing, ETL Testing or Data Architecture. Strong hands-on expertise in DBT, Snowflake and Python – mandatory. Strong experience in ETL/data pipeline testing, data validation, reconciliation and BI/report testing.

Experience designing reusable data automation frameworks and integrating them with CI/CD. Playwright and TypeScript experience – required. Robust knowledge of Azure DevOps, CI/CD and cloud-based data platforms.

Experience with AWS Document Intelligence or similar capabilities. Understanding of AI/GenAI and ability to adopt emerging AI-enabled data testing technologies. Strong analytical, stakeholder management, communication and technical leadership skills. Life Sciences/Pharma and GxP experience is preferred.

Work Experience

7-10Years

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