Data Engineer

BigBear.ai are seeking a highly skilled and motivated Data Engineer to join our Data Architecture & Engineering team.

In this role, you will design and build scalable, secure, and efficient data pipelines that transform raw data into actionable insights.

You’ll work across cloud environments, databases, and development teams to support mission-critical applications, analytics, and reporting.

This position requires expertise in ETL development , AWS cloud services , and database management , along with a strong foundation in Agile software development practices.

• Design and develop end-to-end data pipelines that support ingestion, transformation, and delivery of structured and unstructured data using tools and frameworks aligned with ETL architecture best practices.
• Build and maintain ETL processes that ensure data quality, consistency, and performance across multiple environments.
• Integrate data pipelines with Amazon Web Services (AWS) , leveraging services such as S3, Lambda, Glue, and Redshift to enable scalable and secure data processing.
• Develop and maintain schemas , data dictionaries , and transformation logic to support robust data architecture and documentation.
• Manage and monitor production datasets , ensuring fault tolerance , redundancy , and data integrity across systems.
• Collaborate with cross-functional teams to design and launch new data features, including documentation of dataflows , capabilities , and technical support procedures.
• Support database management and administration tasks such as performance tuning, indexing, and access control.
• Apply Agile software development practices to deliver iterative improvements and respond to evolving data needs.
• Develop and integrate APIs to support data access and interoperability across systems.
• Work with cloud messaging APIs and implement push notification mechanisms where applicable
• Continuously explore and adopt new tools, technologies, and methods to improve data engineering practices and support mission-driven outcomes
• Clearance: Must possess and maintain a TS-SCI clearance
• Bachelor’s degree in computer science, Engineering, Information Systems, or a related field
• 4–8 years of relevant experience in data engineering , ETL development , or database administration
• Proficiency in Amazon Web Services (AWS) and cloud-based data integration
• Strong experience with ETL architecture , data pipeline development , and end-to-end data processing