{"schemaVersion":"jobsearcher.job.v1","id":"f20183917cb2ba0ff983a8f0","url":"https://jobsearcher.com/jobs/f20183917cb2ba0ff983a8f0","canonicalUrl":"https://jobsearcher.com/jobs/f20183917cb2ba0ff983a8f0","title":"Database Engineer","description":"Overview:\n\nBigBear.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.\n\nThis position is remote but may require travel in the DMV area.\n\nWhat you will do:\nBuild source adapters/connectors to ingest data from APIs, legacy systems, databases, and event streams\nDevelop normalization and mapping logic to translate source-specific fields into the common risk-signal schema (including validation, enrichment, and standardization)\nImplement ETL/ELT pipelines with strong engineering rigor: testing, observability, error handling, retries, and backfills\nProduce and consume streaming events (e.g., Kafka topics) to support near-real-time signal delivery and downstream processing\nPartner with data architecture and domain SMEs to define and maintain data contracts, mappings, and lineage from source to normalized signal\nEnsure data quality and consistency (deduplication patterns, schema evolution handling, and reconciliation against source systems)\nOptimize pipeline performance and reliability (throughput, latency, and scalable processing patterns)\nCreate and maintain technical documentation for adapters, transformations, and operational runbooks\nSome travel may be required within the DMV area\nWhat you need to have:\nClearance: Must maintain an active Top Secret security clearance\nBachelor's Degree and 8 to 10 years of experience; Master's Degree and 6 to 8 years of experience\n3–5 years of experience in data engineering, including building production-grade ingestion and transformation pipelines.\nStrong experience with API integrations and ETL/ELT development in complex environments.\nExperience integrating heterogeneous and/or legacy systems with inconsistent schemas and data quality.\nExperience with REST/API frameworks and building maintainable, well-tested integration services.\nWhat we'd like you to have:\nEngineering discipline: writes maintainable, testable code and builds robust pipelines that handle edge cases.\nCuriosity and persistence: digs into messy source data and drives it to consistent outcomes.\nCollaboration: works effectively across data architecture, scoring/analytics, and application teams.\nOperational mindset: builds pipelines that are observable, debuggable, and supportable in production.\nSolid SQL skills and working familiarity with NoSQL data stores.\nProficiency in Python or Java for building data services and transformation logic.\nHands-on experience producing/consuming events in Kafka (producers/consumers) or an equivalent event streaming platform\n\nTools & Technical Skills\n\nAWS Certification – Data Engineer\nGraph Database experience\nSQL and NoSQL databases\nAWS DMS (Database Migration Service)\nAbout BigBear.ai:\n\nBigBear.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.\n\nBigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.","company":"Bigbearai","rawCompany":"bigbearai","city":"McLean","state":"VA","isRemote":false,"isActive":false,"createdAt":"2026-09-02T08:18:26.256Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"},{"code":"15-1242.00","title":"Database Administrators","slug":"database-administrators"}],"industries":[{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Database Engineer","description":"Overview:\n\nBigBear.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.\n\nThis position is remote but may require travel in the DMV area.\n\nWhat you will do:\nBuild source adapters/connectors to ingest data from APIs, legacy systems, databases, and event streams\nDevelop normalization and mapping logic to translate source-specific fields into the common risk-signal schema (including validation, enrichment, and standardization)\nImplement ETL/ELT pipelines with strong engineering rigor: testing, observability, error handling, retries, and backfills\nProduce and consume streaming events (e.g., Kafka topics) to support near-real-time signal delivery and downstream processing\nPartner with data architecture and domain SMEs to define and maintain data contracts, mappings, and lineage from source to normalized signal\nEnsure data quality and consistency (deduplication patterns, schema evolution handling, and reconciliation against source systems)\nOptimize pipeline performance and reliability (throughput, latency, and scalable processing patterns)\nCreate and maintain technical documentation for adapters, transformations, and operational runbooks\nSome travel may be required within the DMV area\nWhat you need to have:\nClearance: Must maintain an active Top Secret security clearance\nBachelor's Degree and 8 to 10 years of experience; Master's Degree and 6 to 8 years of experience\n3–5 years of experience in data engineering, including building production-grade ingestion and transformation pipelines.\nStrong experience with API integrations and ETL/ELT development in complex environments.\nExperience integrating heterogeneous and/or legacy systems with inconsistent schemas and data quality.\nExperience with REST/API frameworks and building maintainable, well-tested integration services.\nWhat we'd like you to have:\nEngineering discipline: writes maintainable, testable code and builds robust pipelines that handle edge cases.\nCuriosity and persistence: digs into messy source data and drives it to consistent outcomes.\nCollaboration: works effectively across data architecture, scoring/analytics, and application teams.\nOperational mindset: builds pipelines that are observable, debuggable, and supportable in production.\nSolid SQL skills and working familiarity with NoSQL data stores.\nProficiency in Python or Java for building data services and transformation logic.\nHands-on experience producing/consuming events in Kafka (producers/consumers) or an equivalent event streaming platform\n\nTools & Technical Skills\n\nAWS Certification – Data Engineer\nGraph Database experience\nSQL and NoSQL databases\nAWS DMS (Database Migration Service)\nAbout BigBear.ai:\n\nBigBear.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.\n\nBigBear.ai is an Equal opportunity employer all protected groups, including protected veterans and individuals with disabilities.","datePosted":"2026-09-02T08:18:26.256Z","dateModified":"2026-09-02T08:18:26.256Z","hiringOrganization":{"@type":"Organization","name":"Bigbearai","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"McLean","addressRegion":"VA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"f20183917cb2ba0ff983a8f0"},"url":"https://jobsearcher.com/jobs/f20183917cb2ba0ff983a8f0"}}