{"id":4267482,"url":"https://alion.io/job/trilogy-federal-data-engineer-2","title":"Data 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":95000,"max":110000,"currency":"USD","period":"year","gross":null,"usd_annual":110000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"Azure","optional":false},{"name":"Azure Data Factory","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Trino","optional":true}],"status":"live","first_seen_at":"2026-11-13T16:49:13Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T16:50:19Z","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 Engineer to support the Department of Veterans Affairs (VA) Summit Advanced Tooling, Lakehouse, and Artificial Intelligence Services (Summit ATLAS) program. The Data Engineer will design, develop, and maintain scalable cloud-based data pipelines and engineering solutions that enable enterprise analytics, reporting, and artificial intelligence and machine learning (AI/ML) capabilities.\nThis position will support modernization of VA's enterprise data environment by integrating diverse data sources into the Summit Data Platform, improving data reliability and accessibility, and delivering secure, high-performance data engineering solutions.\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 scalable data ingestion and processing pipelines using Azure Data Factory (ADF), Azure Databricks, Apache Kafka, and related cloud technologies. \nEngineer and optimize data lakehouse solutions, including Delta Lake architectures, semantic models, conformed dimensions, and partitioning strategies that support enterprise analytics and AI/ML workloads. \nIntegrate data from enterprise systems, legacy platforms, and cloud-based sources using batch, streaming, and event-driven ingestion patterns. \nImplement automated data validation, reconciliation, and monitoring to ensure data accuracy, completeness, consistency, and freshness. \nSupport migration of data pipelines and analytical workloads to Summit, validating parity with source systems and ensuring production readiness. \nOptimize data processing performance, resource utilization, and cloud costs through workload tuning and efficient data architecture. \nCollaborate with data governance specialists to ensure ingested datasets are documented in the Enterprise Data Catalog (EDC), including required metadata, data definitions, and end-to-end lineage. \nImplement Government-approved data governance requirements within engineering solutions, including access controls, data quality standards, and dataset publication criteria. \nDevelop and maintain technical documentation, including pipeline specifications, architecture decisions, operational procedures, and troubleshooting guidance. \nMonitor production pipelines, investigate failures and performance issues, and implement corrective actions to maintain reliable data services. \nMinimum Requirements:\nBachelor's degree in Computer Science, Information Technology, Data Engineering, or a related technical discipline, or an equivalent combination of education and relevant professional experience. \nSeven or more years of professional experience in data engineering, data integration, or enterprise data platform development. \nDemonstrated hands-on experience with Azure Data Factory, Azure Databricks, and Apache Kafka. \nStrong proficiency in Structured Query Language (SQL) and Python for data processing, transformation, and pipeline development. \nExperience designing and maintaining Extract, Transform, and Load (ETL) and Extract, Load, and Transform (ELT) pipelines. \nExperience with cloud-based lakehouse architectures, distributed data processing, and data modeling. \nExperience implementing automated data quality checks, pipeline monitoring, error handling, and performance optimization. \nExperience integrating data governance requirements into engineering workflows, including metadata management, data lineage, and policy-based data access controls. \nFamiliarity with source control, automated testing, and Continuous Integration and Continuous Delivery (CI/CD) practices. \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. \nExperience working within Microsoft Azure Government cloud environments. \nExperience with Azure Synapse Analytics, dedicated SQL pools, or comparable enterprise data warehouse technologies. \nFamiliarity with federated query technologies such as Starburst or Trino. \nExperience migrating complex legacy data warehouse workloads to cloud-based platforms. \nExperience working with sensitive healthcare data and federal privacy and security requirements. \nMicrosoft Certified: Azure Data Engineer Associate or comparable cloud data engineering certification.\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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