{"id":4289842,"url":"https://alion.io/job/trilogy-federal-data-quality-engineer","title":"Data Quality Engineer","company":{"id":4376791,"name":"Trilogy Federal","domain":"trilogyfederal.com","url":"https://alion.io/company/trilogy-federal","size_band":"201-500","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":85000,"max":100000,"currency":"USD","period":"year","gross":null,"usd_annual":100000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Azure","optional":true},{"name":"Databricks","optional":true},{"name":"Delta Lake","optional":true},{"name":"Great Expectations","optional":true}],"status":"live","first_seen_at":"2026-11-13T16:57:21Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T22:54:51Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Trilogy Federal seeks an experienced Data Quality Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (Summit ATLAS) program. The Data Quality Engineer will develop and implement automated data quality controls to ensure the accuracy, completeness, consistency, and reliability of enterprise data used for analytics, reporting, and artificial intelligence and machine learning (AI/ML) applications.\nThis position will support the Summit Data Platform by validating data ingestion and transformation processes, monitoring data quality, and ensuring datasets meet Government-approved standards before publication and customer use.\nPlease note, this position is contingent upon award (anticipated early 2027).This role will also require 1-2 domestic business trips per year.\nPrimary Responsibilities:\nDesign, develop, and maintain automated data quality tests and validation processes for cloud-based data ingestion, transformation, and analytical workloads. \nPerform data reconciliation and equivalence testing between source systems, legacy platforms, and Summit datasets to verify data accuracy and migration parity. \nImplement data quality checks for completeness, consistency, validity, uniqueness, and timeliness in accordance with Government-approved standards. \nDevelop and maintain automated monitoring, anomaly detection, and alerting capabilities to identify data quality issues and pipeline failures. \nValidate compliance with established data freshness and reliability Service Level Agreements (SLAs), documenting test results, exceptions, and residual risks before dataset publication. \nCollaborate with data engineers, data governance specialists, and data owners to implement approved quality rules, thresholds, and publication criteria. \nInvestigate data discrepancies, perform root cause analysis, and coordinate corrective actions to prevent recurring quality issues. \nMaintain data quality rules, test cases, validation results, and supporting documentation in the Data Quality Rule Library and related repositories. \nDevelop and maintain data quality metrics, dashboards, and reports, including contributions to the Summit Data Quality and Ingestion Dashboard. \nSupport production monitoring and release readiness by validating corrective actions, retesting affected datasets, and confirming compliance with established quality standards. \nMinimum Requirements:\nBachelor's degree in Computer Science, Information Technology, Data Analytics, or a related technical discipline, or an equivalent combination of education and relevant professional experience. \nFive or more years of professional experience in data quality engineering, data validation, data testing, or a related discipline. \nStrong proficiency in Structured Query Language (SQL) for data profiling, reconciliation, validation, and analysis. \nExperience developing automated data quality tests and validation scripts using Python or comparable programming languages. \nExperience testing Extract, Transform, and Load (ETL) and Extract, Load, and Transform (ELT) processes in enterprise data environments. \nExperience validating data accuracy, completeness, consistency, and integrity across multiple source systems and data platforms. \nExperience with data reconciliation, regression testing, anomaly detection, and root cause analysis. \nFamiliarity with cloud-based data platforms, data warehouses, and lakehouse architectures. \nExperience documenting data quality rules, test results, defects, and corrective actions. \nStrong analytical, troubleshooting, communication, and collaboration skills. \nAbility to meet VA personnel vetting, background investigation, and system access requirements. \n The ability to travel for 1-2 domestic business trips per year. \nPreferred Qualifications:\nExperience supporting VA or other federal agency data modernization initiatives. \nHands-on experience with Microsoft Azure data services, Azure Databricks, or Delta Lake. \nExperience implementing enterprise data quality frameworks or tools such as Great Expectations, Soda, or comparable technologies. \nKnowledge of Data Management Association (DAMA) data quality principles and enterprise data governance practices. \nExperience implementing data observability solutions and automated quality monitoring for large-scale data pipelines. \nExperience working with sensitive healthcare data and federal privacy and security requirements. \nRelevant certification in data management, data quality, cloud data engineering, or data analytics. \nBenefits (including but not limited to):\nHealth, dental, and vision plans\nOptional FSA\nPaid parental leave\nSafe Harbor 401(k) with employer contributions 100% vested from day 1\nPaid time off and 11 paid holidays\nNo cost group term life/AD&D plan, and optional supplemental coverage\nPet insurance\nMonthly phone and internet stipend\nTuition and training 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