Job Description
Full-time || QA/Test Engineer || Seattle, WA (Hybrid work) Onsite 2-3 days per week Experience Required: 4-6 years
Role Summary: The QA/Test Engineer is responsible for building and executing comprehensive test strategies for all ingestion and ETL pipelines. This role ensures that every pipeline meets the 98-99% data quality pass rate required by the SOW before production promotion, and that automated tests are embedded in the CI/CD process.
Key Responsibilities: - Design and implement a reusable test framework for unit, integration, and end-to-end testing of data ingestion and ETL pipelines.
- Write and maintain unit tests for individual transformation logic, connector behavior, and schema validation.
- Develop integration tests that validate end-to-end data flow from source ingestion through raw → curated → consumption layers.
- Build automated test suites that execute as part of the CI/CD pipeline, gating production deployments.
- Validate data quality check behavior: confirm that DQ rules (completeness, schema conformance, record counts, freshness) correctly trigger fail/alert actions.
- Perform staging environment validation using sample data provided by source owners before production promotion.
- Track and report test coverage, defect rates, and pipeline validation results for each milestone.
- Collaborate with Data/Cloud Engineers to define test cases, edge cases, and acceptance criteria for each data source.
- Support performance and load testing for streaming and high-volume batch sources where representative test data is available.
- Produce test artifacts, test plans, and validation reports as part of milestone documentation.
Required Skills & Qualifications: - 4-6 years of experience in QA/test engineering with a focus on data pipelines, ETL processes, or data platforms.
- Strong proficiency in Python for test automation and data validation scripting.
- Experience with data testing frameworks (e.g., Great Expectations, dbt tests, pytest, or custom frameworks).
- Hands-on experience testing data pipelines on AWS (Glue, Spark, S3, Athena, Redshift).
- Understanding of data quality dimensions: completeness, accuracy, consistency, freshness, schema conformance.
- Experience integrating automated tests into CI/CD pipelines (GitHub Actions, CodePipeline, Jenkins).
- Ability to write SQL queries for data validation and reconciliation.
- Familiarity with test data management strategies for sensitive or regulated data.
- Strong documentation skills for test plans, test cases, and validation reports.
- Experience working in Agile/Scrum teams with 2-week sprint cycles.
Preferred Skills: - Experience with performance/load testing for data pipelines.
- Familiarity with contract testing for APIs and schema registries.
- Knowledge of data observability tools (Monte Carlo, Datafold, or similar).
Job Tags
Full time, Contract work, 2 days per week, 3 days per week