[Hiring] Data Engineer @Aptive

Role Description

As a Data Engineer supporting the National Training and Support Program (NTSP) Quality and Data Informatics initiative, you will design, build, and maintain enterprise-grade data pipelines and ETL/ELT processes that power critical healthcare analytics within the Department of Veterans Affairs (VA). This role sits at the intersection of cloud data engineering and federal health informatics, enabling bidirectional data movement across VA enterprise data warehouses, cloud workgroups, and operational systems to support data-driven decisions that directly impact Veteran care.

The ideal candidate is a technically rigorous and self-directed data engineer who thrives in complex, multi-source healthcare data environments and takes pride in writing clean, well-documented code and pipelines. You bring a collaborative mindset, strong attention to data quality and governance, and the ability to navigate both technical stakeholders and mission-driven federal program requirements.

Qualifications

• 8+ years of relevant experience in data engineering, including design and development of ETL/ELT pipelines and cloud-based data environments (or 13+ years of relevant experience in lieu of a BA/BS degree).
• BA/BS degree in Computer Science, Information Systems, Data Science, or a related technical field required; 5 years of additional relevant experience may be substituted for the degree requirement.
• Prior experience supporting federal agency programs, preferably within the Department of Veterans Affairs (VA), Department of Defense (DoD), or another federal health or human services agency.
• Ability to obtain and maintain a VA Position of Public Trust clearance; must be able to comply with VA information security, privacy, and system access requirements including completing required VA training and onboarding.
• Must be a U.S. citizen or authorized to work in the United States in compliance with federal contracting requirements applicable to this program.
• Demonstrated proficiency in SQL or Spark SQL for data transformation and querying, with hands-on experience implementing record-linkage or patient-matching logic across multi-source or multi-facility datasets.

Requirements

• Design, build, test, and maintain scalable data pipelines and ETL/ELT processes supporting cloud-based data environments, including bidirectional data movement between VA enterprise data warehouses, cloud workgroups, and operational systems.
• Implement patient-matching and record-linkage logic across multiple identifiers to ensure accurate, deduplicated Veteran data across disparate source systems and facilities.
• Harmonize datasets across VA facilities and data sources, resolving structural, semantic, and format inconsistencies to produce analysis-ready, high-quality data assets.
• Develop and maintain comprehensive data flow documentation, administrator guides, and technical documentation in accordance with federal contracting and VA documentation standards.
• Provide ongoing pipeline support and maintenance, including troubleshooting data quality issues, optimizing performance, and executing transition planning to ensure continuity of data operations across program phases.
• Collaborate with data analysts, informatics specialists, and program stakeholders to translate business and reporting requirements into scalable data engineering solutions, including Power BI report development leveraging Databricks SparkSQL.

Benefits

• Hands-on experience with Azure Databricks and PySpark for large-scale distributed data processing in a cloud healthcare environment.
• Proficiency in Python for pipeline automation, data wrangling, and scripting within VA or federal health data contexts.
• Experience developing Power BI reports and dashboards using Databricks SparkSQL as a data source, supporting operational or clinical quality metrics.
• Familiarity with non-Microsoft automation platforms such as Salesforce or Red Hat products (e.g., Ansible, OpenShift) integrated into federal data workflows.
• Knowledge of VA or federal healthcare data standards (e.g., HL7, FHIR, CDW, Corporate Data Warehouse) and experience harmonizing clinical or administrative datasets across facilities.