This 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.
Please note, this position is contingent upon award (anticipated early 2027). This role will also require 1-2 domestic business trips per year.
Primary Responsibilities:
- Design, develop, and maintain automated data quality tests and validation processes for cloud-based data ingestion, transformation, and analytical workloads.
- Perform data reconciliation and equivalence testing between source systems, legacy platforms, and Summit datasets to verify data accuracy and migration parity.
- Implement data quality checks for completeness, consistency, validity, uniqueness, and timeliness in accordance with Government-approved standards.
- Develop and maintain automated monitoring, anomaly detection, and alerting capabilities to identify data quality issues and pipeline failures.
- Validate compliance with established data freshness and reliability Service Level Agreements (SLAs), documenting test results, exceptions, and residual risks before dataset publication.
- Collaborate with data engineers, data governance specialists, and data owners to implement approved quality rules, thresholds, and publication criteria.
- Investigate data discrepancies, perform root cause analysis, and coordinate corrective actions to prevent recurring quality issues.
- Maintain data quality rules, test cases, validation results, and supporting documentation in the Data Quality Rule Library and related repositories.
- Develop and maintain data quality metrics, dashboards, and reports, including contributions to the Summit Data Quality and Ingestion Dashboard.
- Support production monitoring and release readiness by validating corrective actions, retesting affected datasets, and confirming compliance with established quality standards.
Minimum Requirements:
- Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a related technical discipline, or an equivalent combination of education and relevant professional experience.
- Five or more years of professional experience in data quality engineering, data validation, data testing, or a related discipline.
- Strong proficiency in Structured Query Language (SQL) for data profiling, reconciliation, validation, and analysis.
- Experience developing automated data quality tests and validation scripts using Python or comparable programming languages.
- Experience testing Extract, Transform, and Load (ETL) and Extract, Load, and Transform (ELT) processes in enterprise data environments.
- Experience validating data accuracy, completeness, consistency, and integrity across multiple source systems and data platforms.
- Experience with data reconciliation, regression testing, anomaly detection, and root cause analysis.
- Familiarity with cloud-based data platforms, data warehouses, and lakehouse architectures.
- Experience documenting data quality rules, test results, defects, and corrective actions.
- Strong analytical, troubleshooting, communication, and collaboration skills.
- Ability to meet VA personnel vetting, background investigation, and system access requirements.
- The ability to travel for 1-2 domestic business trips per year.
Preferred Qualifications:
- Experience supporting VA or other federal agency data modernization initiatives.
- Hands-on experience with Microsoft Azure data services, Azure Databricks, or Delta Lake.
- Experience implementing enterprise data quality frameworks or tools such as Great Expectations, Soda, or comparable technologies.
- Knowledge of Data Management Association (DAMA) data quality principles and enterprise data governance practices.
- Experience implementing data observability solutions and automated quality monitoring for large-scale data pipelines.
- Experience working with sensitive healthcare data and federal privacy and security requirements.
- Relevant certification in data management, data quality, cloud data engineering, or data analytics.
Benefits (including but not limited to):
- Health, dental, and vision plans
- Optional FSA
- Paid parental leave
- Safe Harbor 401(k) with employer contributions 100% vested from day 1
- Paid time off and 11 paid holidays
- No cost group term life/AD&D plan, and optional supplemental coverage
- Pet insurance
- Monthly phone and internet stipend
- Tuition and training reimbursement
Skills Required
- Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a related technical discipline, or equivalent education and relevant professional experience
- Five or more years of professional experience in data quality engineering, data validation, data testing, or a related discipline
- Strong proficiency in SQL for data profiling, reconciliation, validation, and analysis
- Experience developing automated data quality tests and validation scripts using Python or comparable programming languages
- Experience testing ETL and ELT processes in enterprise data environments
- Experience validating data accuracy, completeness, consistency, and integrity across multiple source systems and data platforms
- Experience with data reconciliation, regression testing, anomaly detection, and root cause analysis
- Familiarity with cloud-based data platforms, data warehouses, and lakehouse architectures
- Experience documenting data quality rules, test results, defects, and corrective actions
- Strong analytical, troubleshooting, communication, and collaboration skills
- Ability to meet VA personnel vetting, background investigation, and system access requirements
- Ability to travel for 1-2 domestic business trips per year
- Experience supporting VA or other federal agency data modernization initiatives
- Hands-on experience with Microsoft Azure data services, Azure Databricks, or Delta Lake
- Experience implementing enterprise data quality frameworks or tools such as Great Expectations, Soda, or comparable technologies
- Knowledge of DAMA data quality principles and enterprise data governance practices
- Experience implementing data observability solutions and automated quality monitoring for large-scale data pipelines
- Experience working with sensitive healthcare data and federal privacy and security requirements
- Relevant certification in data management, data quality, cloud data engineering, or data analytics
What We Do
Founded in 2009 and headquartered in the Washington DC metro area, Trilogy Federal is a verified service-disabled, veteran-owned small business (SDVOSB) providing financial management and information technology consulting to the Federal government. Trilogy has an extensive and distinctive history helping Federal clients achieve their financial management goals. Our leadership team has over 60 years of combined experience supporting Federal financial management initiatives. Our professional staff specializes in federal financial management and maintains certifications in several relevant programs. Trilogy strives to provide its clients with a flexible and comprehensive approach to financial management with the ultimate goal of fiscal compliance and audit readiness. The Trilogy approach starts with assessing the financial management solution and determining its effectiveness in capturing functional business requirements and meeting agency reporting requirements. Since our inception, we have assisted our federal partners in migrating to new financial management systems or enhancing existing systems to meet new requirements. Ultimately, success lies in the data, where Trilogy utilizes industry leading Business Intelligence and Business Performance Management tools to assess the overall effectiveness of financial business operations and to produce timely, reliable and value-added financial reporting. We have a proven track record of successful implementations for agencies large and small.
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