QA Engineer - ETL
Algoworks (company site, opens in a new tab)On-siteDirect career pageEst. 6–12 LPA
Posted 12h ago
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Job description
Structured overview of role & requirements
About This Role
- Ensure accuracy, completeness, and reliability of data pipelines and analytics outputs in high-volume, event-driven domains such as public safety and healthcare.
- Perform source-to-target data reconciliation, validate KPIs, detect anomalies, and maintain referential integrity across datasets and reporting layers.
- Develop and maintain automated data validation frameworks in Python, integrate validation in CI/CD workflows, and leverage AI-assisted tools with human verification to enhance data quality tests.
Minimum Requirements
- Strong SQL skills including joins, aggregation, window functions, and profiling for data validation.
- Strong hands-on Python experience for test automation and data validation beyond scripting.
- Experience in ETL/ELT QA, data testing, analytics validation, or data quality engineering.
- Understanding of event-driven/transaction-based systems and common data pipeline failure patterns.
Ideal Candidate Profile
- Experienced in validating large datasets and reporting layers with high reliability and accuracy demands.
- Proficient in building and integrating automated data validation frameworks, preferably with Great Expectations or custom Python frameworks.
- Skilled in collaborating with engineering teams to quickly identify root causes and verify fixes, reducing incident triage time.