Manager - ETL Testing & Test Data Management

Leads ETL/Data Testing and Test Data Management initiatives by working closely with SQM, Development, Data, and Business Partners to ensure the delivery of high-quality data and reliable data pipelines. Acquires a deep understanding of data architecture, ETL processes, data flows, and test data requirements to ensure comprehensive and effective testing. Collaborates with development and testing teams to establish data testing strategies, standards, and reusable frameworks that support functional, integration, regression, and end-to-end testing.

Identifies opportunities to improve ETL testing and Test Data Management processes and recommends enhancements to testing methods, tools, automation, and frameworks. Drives the adoption of innovative technologies, including AI agents, for test case generation, data validation, anomaly detection, and synthetic test data creation. Collaborates with SQM teams to ensure data testing and test data practices align with SDLC standards and remain reusable across projects.

Collaborates with SQM leadership to ensure appropriate allocation of resources across ETL Testing and Test Data Management activities. Works closely with Development, Data, and Business teams to establish priorities and facilitate decisions pertaining to data quality and testing.

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* Key Responsibilities:

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* + Lead, mentor, grow ETL Testing and Test Data Management teams, ensuring high performance, clear priorities, and career development for team members.

+ Own the end-to-end test strategy for ETL/data pipelines - covering source-to-target validation, transformation logic, data completeness, accuracy, reconciliation, and performance testing.

+ Drive data lineage validation and data comparison testing using Ab Initio and oversee testing of Oracle-based ETL jobs built on ODI (Oracle Data Integrator).

+ Define and drive the Test Data Management strategy, including data provisioning, sub setting, masking/anonymization, synthetic data generation, and data refresh processes across environments.

+ Champion automation-first testing - evaluate, adopt, and build tools/frameworks (including AI-driven/agentic solutions) to reduce manual testing effort and increase test coverage.

+ Explore and implement AI agents to automate repetitive data testing tasks such as test case generation, data profiling, anomaly detection, schema drift detection, and synthetic test data creation.

+ Partner closely with Data Engineering, BI/Analytics, and Product teams to embed quality checks early in the data pipeline lifecycle (shift-left testing).

+ Establish metrics, dashboards, and reporting to track test coverage, defect trends, data quality KPIs, and team productivity.

+ Manage stakeholder relationships, set delivery timelines, and ensure testing milestones align with overall project/program schedules.

+ Stay current with emerging trends in data quality engineering, test automation, and AI/ML-based testing tools, and bring innovative ideas into the team's roadmap.

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* Experience and Skills:

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* + 10+ years of overall experience in QA/Testing, with strong hands-on experience in ETL/Data Testing, SQL, data warehousing concepts, and data integration testing.

+ Mandatory hands-on experience with Informatica for building and validating ETL workflows/mappings and performing data integration testing.

+ Mandatory hands-on experience with Ab Initio, specifically for data lineage tracking and data comparison across source and target systems.

+ Mandatory hands-on experience with Oracle Data Integrator (ODI) for testing and validating Oracle-based ETL jobs and data pipelines.

+ 5+ years of experience in Test Data Management, including data masking, subsetting, synthetic data generation, data provisioning, and TDM tools such as Informatica TDM, CA Test Data Manager, or similar.

+ Proven experience leading and managing testing teams, including ETL testing, Test Data Management, or cross-functional data quality teams.

+ Strong SQL skills and solid understanding of data warehousing, data lakes, and cloud data platforms such as Snowflake, Redshift, Big Query, Databricks, or similar technologies.

+ Demonstrated experience with test automation for data pipelines, including Python/PySpark frameworks, dbt tests, Great Expectations, or similar tools. Exposure to scripting and development of custom testing and automation utilities is preferred.

+ Working knowledge of or hands-on experience with CI/CD pipelines and integrating automated data testing into deployment workflows.

+ Working…