Quality Assurance Analyst / ETL Tester - Enterprise Data Warehouse
Vergence -null, United States
The ETL Tester will be responsible for designing, automating, and executing test cases for Enterprise Data Warehouse (EDW) ETL processes in a State Government Medicaid environment. In this role, you will be responsible for ensuring the accuracy, integrity, and reliability of data as it moves through our ETL processes. You will leverage your expertise to design and execute test strategies that validate both functional and non-functional requirements of our data pipelines.
The tester will leverage ETL tools — primarily Informatica PowerCenter for extraction, transformation, and loading, and Teradata RDBMS for core data store validation — within Azure DevOps and agile sprint cycles to ensure data quality, identify defects, and automate repeatable testing processes.
Key Responsibilities:
Requirement Analysis
- Review Change Requests (CRs) and participate in requirement analysis for new EDW extracts and transformations.
- Participate in data modeling and requirement gathering sessions to ensure testing aligns with business needs.
Data Validation
- Perform backend testing to compare data in source systems to target Medicaid Enterprise Data Warehouses (EDW).
- Verify source-to-target data mapping and transformation logic for Medicaid datasets.
- Validate data quality, standardization rules, and loading accuracy.
SQL & Scripting
- Write complex SQL queries (including multi-table JOINs, aggregations) to validate ETL outputs against business rules.
- Conduct row counts, null checks, duplicate checks, referential integrity validation.
- Design test plans, test cases, and test scenarios for ETL processes.
- Document test results and provide detailed feedback to stakeholders, highlighting areas for improvement.
- Execute manual and automated tests for both full-load and incremental-load cycles.
- Identify, document, and track discrepancies using tools like JIRA, HP ALM, or Azure DevOps Test Plans.
- Collaborate with ETL developers to resolve defects and perform regression testing. Automation.
- Develop automated database validation scripts using Python, SQL Alchemy, and Pandas.
- Create shell scripts for ETL monitoring and log analysis.
- Integrate automation into CI/CD pipelines in Azure DevOps.