Job Description
Job Summary
We are seeking an experienced ETL Tester to ensure the quality, accuracy, and reliability of data across enterprise data platforms. The ideal candidate will have strong handson experience in ETL testing and database testing, with a proven background in healthcare or medical claims data environments.
This role involves close collaboration with data engineers, developers, business analysts, and QA teams to validate data pipelines, transformations, and downstream reporting systems across the full data lifecycle.
Key Responsibilities
ETL & Data Testing
Review data requirements, sourcetotarget mappings, and design documents to create test scenarios.
Validate data extraction, transformation, and loading (ETL) processes for accuracy, completeness, and consistency.
Perform data reconciliation between source systems, staging layers, and target data warehouses/data marts.
Analyze data anomalies, transformation logic issues, and load failures, and report defects with clear root cause analysis.
Validate healthcare data for business rules, data integrity, and regulatory compliance.
Design, develop, and execute automated ETL test scripts for data validation and regression testing.
Execute manual ETL and data tests for complex business logic and exception scenarios.
Use SQL extensively to validate joins, aggregations, calculations, and historical data loads.
Collaboration & Quality Assurance
Work closely with crossfunctional teams to ensure endtoend data quality.
Participate in Agile ceremonies, including sprint planning, backlog grooming, and defect triage.
Document test cases, test results, and defect metrics using test management tools.
Assist in troubleshooting production data issues and support root cause analysis.
Required Qualifications
Education & Experience
Bachelor's degree or equivalent professional experience.
5+ years of QA / Data Testing experience.
3+ years of handson ETL and Data Testing experience.
Overall 5+ years of professional IT experience.
Clarification
The candidate should have at least 5+ years of overall QA/Data Testing experience, within which a minimum of 3+ years must be handson ETL and data testing. The overall IT experience reflects broader exposure across roles such as QA, development, data engineering, analytics, or related IT functions.
Technical Skills
Strong experience in ETL testing and database testing using SQL.
Proficiency in Playwright is mandatory.
Handson experience with test automation tools (e.g., Selenium or equivalent frameworks).
Clarifications On Automation Expectations
This role is primarily focused on ETL and data automation, not UI automation.
Selenium or similar tools are referenced to indicate an automation mindset; the core focus is data pipeline validation, not frontend UI testing.
Expected Automation Includes
Advanced SQLbased automation (joins, aggregations, calculations, historical loads)
Sourcetotarget reconciliation and rowcount/data quality checks
Python or similar scripting for data comparison, regression checks, and orchestration
Automation across staging, warehouse, and downstream marts
Exposure to Azurebased cloud data environments
The Candidate Is Expected To
Design and develop ETL/data test automation
Maintain and enhance automation suites
Execute automated and manual ETL tests
Analyze results and perform root cause analysis
Clearly document defects and collaborate with stakeholders
Experience validating largescale datasets in data warehouses or analytical platforms
Familiarity with test management tools and defect tracking systems
Domain Experience
Healthcare insurance industry experience
Medical Claims Data Experience Is Required
Key Competencies
Strong analytical and problemsolving skills
Excellent communication and documentation abilities
High attention to detail with a datafirst mindset
Ability to work independently in complex data environments
Proven collaboration skills across technical and business teams
Preferred Qualifications
Experience testing data pipelines supporting reporting, analytics, or regulatory submissions
Knowledge of Agile / Scrum methodologies
Understanding of data governance, data quality frameworks, and audit controls
