Data Engineer

Overview

BigBear.ai is hiring Data Engineers to build and maintain the source adapters and normalization logic that translate raw data from disparate systems into a common risk-signal schema. This position focuses on reliable ingestion and transformation—turning heterogeneous legacy inputs (APIs, feeds, databases, files, and event streams) into consistent, high-quality signals that downstream scoring and adjudication workflows can trust. This position is remote but will require travel in the DMV area. What you will do - Build source adapters/connectors to ingest data from APIs, legacy systems, databases, and event streams - Develop normalization and mapping logic to translate source-specific fields into the common risk-signal schema (including validation, enrichment, and standardization) - Implement ETL/ELT pipelines with strong engineering rigor: testing, observability, error handling, retries, and backfills - Produce and consume streaming events (e.g., Kafka topics) to support near-real-time signal delivery and downstream processing - Partner with data architecture and domain SMEs to define and maintain data contracts, mappings, and lineage from source to normalized signal - Ensure data quality and consistency (deduplication patterns, schema evolution handling, and reconciliation against source systems) - Optimize pipeline performance and reliability (throughput, latency, and scalable processing patterns) - Create and maintain technical documentation for adapters, transformations, and operational runbooks - Some travel may be required within the DMV area What you should have - Clearance: Must maintain an active Top Secret security clearance - Bachelor's Degree and 5 to 8 years of experience with a Bachelor's degree, equivalent experience may be accepted in lieu of a degree - 3+ years of experience in data engineering, including building production-grade ingestion and transformation pipelines - Strong experience with API integrations and ETL/ELT development in complex environments - Experience integrating heterogeneous and/or legacy systems with inconsistent schemas and data quality - Experience with REST/API frameworks and building maintainable, well-tested integration services What we'd like you to have - Engineering discipline: writes maintainable, testable code and builds robust pipelines that handle edge cases - Curiosity and persistence: digs into messy source data and drives it to consistent outcomes - Collaboration: works effectively across data architecture, scoring/analytics, and application teams - Operational mindset: builds pipelines that are observable, debuggable, and supportable in production - Solid SQL skills and working familiarity with NoSQL data stores - Proficiency in Python or Java for building data services and transformation logic - Hands-on experience producing/consuming events in Kafka (producers/consumers) or an equivalent event streaming platform Tools & Technical Skills - AWS Certification – Data Engineer - Graph Database experience - SQL and NoSQL databases - AWS DMS (Database Migration Service) About BigBear.ai BigBear.ai is a leading provider of AI-powered decision intelligence solutions for national security, supply chain management, and digital identity. Customers and partners rely on Bigbear.ai’s predictive analytics capabilities in highly complex, distributed, mission-based operating environments. Headquartered in McLean, Virginia, BigBear.ai is a public company traded on the NYSE under the symbol BBAI. For more information, visit https://bigbear.ai/ and follow BigBear.ai on LinkedIn: @BigBear.ai and X: @BigBearai. BigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.