Data Analyst/QA Engineer
Summary
Designs and maintains automated data quality checks using AWS Glue and Deequ, monitors ETL pipelines, performs schema validation, and executes automated tests; core technologies include AWS Glue, Deequ, SQL, and Python.
Responsibilities
- Design, develop, and maintain automated data quality checks using AWS Glue and Deequ
- Perform schema validation and manage data load exceptions
- Monitor production ETL pipelines and ensure zero data loss
- Create and execute automated test cases for platform functionality
- Conduct static code analysis and security scans
- Support the agency's Independent Verification and Validation (IV&V) and User Acceptance Testing (UAT) processes
- Validate ETL metadata, data models, and documentation
- Support ad hoc data requests with optimized queries and reports
- Maintain team performance metrics dashboards
- Participate in agile ceremonies using JIRA and GitHub
- Bachelor's degree in Computer Science, Information Systems, Data Analytics, or related field
- 3-5 years of experience in data quality engineering, QA engineering, or data analytics
- Proficiency in SQL for data validation and query development
- Experience with Python for test scripting and data analysis
- Experience with AWS Glue, Deequ, or Great Expectations
- Hands‑on experience with CI/CD-integrated automated testing frameworks
- US Citizenship required
- Ability to work 8am-5pm Eastern Time
- Ability to obtain a federal public trust suitability determination
- Direct federal program experience
- Experience with Trino, Athena, or equivalent query engines
- Familiarity with XML schema validation
- Knowledge of FISMA, NIST 800-53, and OWASP ASVS
- Experience with large‑scale financial or regulatory datasets
- Familiarity with Section 508 accessibility standards
Simple Technology Solutions (STS) provides exceptional solutions to Federal Government clients. Recognized as a \"Best Place to Work,\" STS fosters a culture of collaboration, continuous learning, and excellence.