Quality Engineer (Data)

Role overview Join a data engineering team supporting a program that manages financial and regulatory data, where you will shape quality assurance across modern data pipelines and analytics platforms. This role blends hands-on test engineering with data engineering fundamentals, applying rigor suited to highly governed data. You will partner with engineers, analysts, scientists, and stakeholders to keep datasets accurate, complete, and trustworthy.

Responsibilities - Develop and maintain data quality strategies, standards, documentation, and testing practices for pipelines and analytical datasets. - Design and execute automated and manual tests covering accuracy, completeness, integrity, uniqueness, schema consistency, business rules, freshness, and statistical validity. - Build reusable quality checks and integration or end-to-end tests using Python, PySpark or Spark, SQL, and Apache Airflow. - Validate transformations across Apache Spark, Python, and AWS data services such as Amazon S3. - Investigate anomalies, schema drift, missing data, and pipeline failures, partnering with data engineers on root cause and resolution. - Collaborate across the SDLC to translate business and regulatory requirements into quality controls, support UAT, release validation, and production deployments.

Requirements - Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent experience. - 7+ years of professional experience in software quality assurance, testing, or quality engineering. - Strong Python programming and hands-on experience building automated tests with Pytest or a comparable framework. - Solid grasp of data quality principles including accuracy, completeness, consistency, uniqueness, validity, and timeliness. - Experience with relational databases, SQL, and testing data pipelines or large-scale ETL/ELT processes. - Experience with workflow orchestration such as Airflow and cloud-based data platforms, preferably AWS. - Comfort supporting Agile teams and communicating technical data issues to non-technical stakeholders.

Nice to have - Background testing financial, securities, regulatory, or similarly governed data. - Familiarity with AWS services like S3, Glue, Redshift, and Athena; dbt; CI/CD pipelines; and schema evolution or drift detection. - Experience with data lineage, metadata management, observability, or data quality frameworks. - Federal government project experience, or certifications such as CSTE or ISTQB.

Benefits and work setup - Remote work available, with hybrid roles noted per posting. - Estimated salary range of $75,000 to $110,000 annually, depending on experience and skills. - Medical, dental, and vision coverage; life insurance; short- and long-term disability. - Employee Assistance Program, 401(k) with 4% match, and a liberal PTO policy. - Annual continuing education and wellness budgets, plus referral and performance-based bonus programs. - Eligibility: U.S. citizenship and ability to obtain Public Trust clearance.