Data Engineer
Washington, DC - Hybrid
Position Summary
Data Engineers design and build automated data pipelines that support Government’s analytics, AI, and automation initiatives. These individuals are responsible for ETL/ELT processes, data quality implementation, and ensuring governed, reliable data flows from source systems to analytical platforms and AI models.
Key Responsibilities
• Design and build automated ETL/ELT pipelines using SQL, Python, and Azure Data Factory
• Develop data pipelines supporting Power BI dashboards and AI/automation use cases
• Implement data validation rules and quality monitoring processes
• Create and maintain data flow documentation including lineage and transformation logic
• Build repeatable data refresh processes with scheduled automation
• Support data integration across Government's siloed systems into unified platforms
• Implement data cleansing, transformation, and reconciliation processes
• Collaborate with Data Scientists on data pipeline requirements for ML workflows
• Support data catalog and metadata management initiatives
• Ensure data pipelines comply with governance policies and security requirements
• Monitor pipeline performance and troubleshoot data issues
• Document data architectures and pipeline configurations
Required Qualifications
• Education: Bachelor's degree in Computer Science, Data Engineering, or related field
• Experience: 6+ years building automated ETL/ELT pipelines in enterprise environments
• Certifications:
- Azure Data Engineer Associate (DP-203) and/or equivalent cloud data certification
• Technical Skills:
- Expert proficiency in SQL and Python for data engineering
- Experience with Azure Data Factory, Azure Synapse, or equivalent cloud data tools
- Knowledge of data warehouse and data lake architectures
- Experience with data quality frameworks and monitoring tools
- Familiarity with Power BI data model requirements
- Understanding of data governance principles and metadata management
Preferred Qualifications
• Experience in federal government data environments
• Knowledge of compliance-driven data handling requirements
• Experience with real-time data streaming technologies
• Familiarity with Master Data Management (MDM) concepts
