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
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Develop normalization and mapping logic to translate source-specific fields into the common risk-signal schema (including validation, enrichment, and standardization)
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Implement ETL/ELT pipelines with strong engineering rigor: testing, observability, error handling, retries, and backfills
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Produce and consume streaming events (e.g., Kafka topics) to support near-real-time signal delivery and downstream processing
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Partner with data architecture and domain SMEs to define and maintain data contracts, mappings, and lineage from source to normalized signal
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Ensure data quality and consistency (deduplication patterns, schema evolution handling, and reconciliation against source systems)
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Optimize pipeline performance and reliability (throughput, latency, and scalable processing patterns)
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Create and maintain technical documentation for adapters, transformations, and operational runbooks
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Some travel may be required within the DMV area
What you need to have:
- Clearance: Must maintain an active Top Secret security clearance
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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
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3+ years of experience in data engineering, including building production-grade ingestion and transformation pipelines.
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Strong experience with API integrations and ETL/ELT development in complex environments.
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Experience integrating heterogeneous and/or legacy systems with inconsistent schemas and data quality.
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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.
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Curiosity and persistence: digs into messy source data and drives it to consistent outcomes.
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Collaboration: works effectively across data architecture, scoring/analytics, and application teams.
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Operational mindset: builds pipelines that are observable, debuggable, and supportable in production.
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Solid SQL skills and working familiarity with NoSQL data stores.
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Proficiency in Python or Java for building data services and transformation logic.
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Hands-on experience producing/consuming events in Kafka (producers/consumers) or an equivalent event streaming platform
Tools & Technical Skills
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AWS Certification – Data Engineer
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Graph Database experience
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SQL and NoSQL databases
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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.