Opportunities in United States

SteerBridge is a modern technology company delivering innovative, mission‑focused solutions to the U.S. Government and private sector. Leveraging deep expertise in federal acquisition, digital transformation, and emerging technologies, we deliver agile, commercial‑grade capabilities that accelerate operational effectiveness and drive measurable mission success. At the core of SteerBridge is our people—especially the veterans whose leadership, problem‑solving mindset, and commitment to excellence elevate every project we support. We don’t simply hire exceptional talent; we cultivate it, creating meaningful career pathways for veterans, military spouses, and professionals who share our passion for advancing technology and strengthening the missions we serve.

SteerBridge is seeking a Data Engineer (Mid-Level, 3+ years) to join our growing Aviation team at our headquarters in Tysons Corner (Vienna, VA). In this role, you will support a major federal transformation effort by modernizing and optimizing complex data systems at scale, working alongside architects, analysts, and data scientists to design efficient data flows, enhance data quality, and ensure secure, reliable pipelines for both real-time and batch processing environments. Our projects span AI/ML, cloud architecture, and large-scale data engineering to help modernize critical federal systems. This is a full-time, on-site position based in Vienna, VA (3-5 days/week on-site; hybrid arrangements available at supervisors' discretion).

Design, build, optimize, and maintain scalable batch and real-time ETL/ELT pipelines for structured and unstructured data across complex, distributed systems. Develop and manage modern data lake and cloud-based data architectures using platforms such as AWS S3 and Azure Blob Storage, including support for API-based data integration. Implement data transformation, workflow automation, and orchestration using technologies such as dbt, Informatica, Azure Data Factory, Databricks, AWS Glue, EventBridge, and S3 Event Notifications. Develop performant SQL queries and Python or JavaScript scripts for data ingestion, parsing, transformation, cleanup, and processing. Conduct data profiling, linkage, validation, and quality checks while maintaining data lineage, governance, security, compliance, and performance standards across data environments. Collaborate with data scientists, software engineers, and stakeholders to deliver reliable data products supporting analytics, reporting, and model development. Maintain technical documentation for pipelines, data structures, infrastructure, standards, and data products while mentoring junior engineers through technical guidance, code reviews, and engineering best practices.

Eligibility requirements: U.S. citizenship is required for this position under applicable federal contract requirements. Candidates must also be able to obtain and maintain the security clearance required for the role. Bachelor’s degree in Computer Science or a related field, with a minimum of 3 years of relevant professional experience. Strong proficiency in Python and SQL, with hands-on experience using Pandas, PySpark, and AWS Glue. Strong understanding of ETL/ELT frameworks, data lake design, and cloud-based data architectures. Familiarity with both real-time and batch data processing tools and methodologies. Experience implementing data governance, data quality, security, and compliance standards within data environments. Ability to appropriately safeguard sensitive information and comply with applicable organizational security and privacy requirements. Candidates must be located in the Vienna, VA area and able to work on-site at the Vienna, VA office 3–5 days per week. Hybrid arrangements may be available at the supervisor’s discretion.

Experience with dbt, Informatica, Azure Data Factory, and Databricks for data transformation and workflow automation. Experience with AWS orchestration services such as EventBridge and S3 Event Notifications. Experience mentoring junior engineers and leading the design of scalable ETL/ELT processes across complex, distributed systems. Familiarity with multi-cloud data processing environments, including AWS S3 and Azure Blob Storage, as well as API-based data integration.