Data Engineer

About this job: Residency All applicants must reside in the United States at the time of application.

Overview: BigBear.aiare seeking a highly skilled and motivated Data Engineerto join our Data Architecture & Engineering team. In this role, you will design and build scalable, secure, and efficientdata pipelinesthat transformraw datainto actionable insights. You’ll work across cloud environments, databases, and development teams to support mission‑critical applications, analytics, and reporting. This position requires expertise inETL development , AWS cloud services, anddatabase management, along with a strong foundation inAgile software developmentpractices.

What you will do: Design and develop end-to-end data pipelinesthat support ingestion, transformation, and delivery of structured and unstructured data using tools and frameworks aligned withETL architecturebest practices. Build and maintainETL processesthat ensure data quality, consistency, and performance across multiple environments. Integrate data pipelines withAmazon Web Services (AWS), leveraging services such as S3, Lambda, Glue, and Redshift to enable scalable and secure data processing. Develop and maintainschemas , data dictionaries, and transformation logic to support robustdata architectureand documentation. Manage and monitorproduction datasets, ensuringfault tolerance , redundancy, anddata integrityacross systems. Collaborate with cross‑functional teams to design and launch new data features, including documentation ofdataflows , capabilities, andtechnical supportprocedures. Supportdatabase management and administrationtasks such as performance tuning, indexing, and access control. ApplyAgile software developmentpractices to deliver iterative improvements and respond to evolving data needs. Develop and integrateAPIsto support data access and interoperability across systems. Work withcloud messaging APIsand implementpush notificationmechanisms where applicable. Continuously explore and adopt new tools, technologies, and methods to improvedata engineeringpractices and support mission‑driven outcomes. What you need to have

Clearance: Must possess and maintain a TS‑SCI clearanceBachelor’s degree in computer science, Engineering, Information Systems, or a related field4–8 years of relevant experience indata engineering , ETL development, ordatabase administrationProficiency inAmazon Web Services (AWS)and cloud-based data integrationStrong experience withETL architecture , data pipeline development, andend‑to‑end data processingSolid understanding ofdatabase management, including schema design, indexing, and optimizationExperience withAPI developmentand integrationAbility to manage and transformraw datainto usable formats for analytics and reportingFamiliarity withAgile methodologiesand collaborative development environmentsStrong problem‑solving skills, attention to detail, and ability to providetechnical supportfor data systems What we'd like you to have Experience withcloud messaging APIsandpush notification systems Hands‑on experience withdatabase administrationand performance tuning Keen interest in learning and applying the latestdata tools and technologiesto solve real‑world problems Experience supportingtechnical supportfunctions related to data infrastructure Familiarity withnational securityor mission‑driven data environments Pay transparency Please note the targeted compensation range is provided as an estimate, and any actual compensation offer may vary depending on the needs of the company, or an applicant's skillset, competencies, experience, education, certifications, location, or other factors. The estimated range does not include the value of any benefits offered. About BigBear.aiBigBear.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.

Clearance: Must possess and maintain a TS‑SCI clearanceBachelor’s degree in computer science, Engineering, Information Systems, or a related field4–8 years of relevant experience indata engineering , ETL development, ordatabase administrationProficiency inAmazon Web Services (AWS)and cloud-based data integrationStrong experience withETL architecture , data pipeline development, andend‑to‑end data processingSolid understanding ofdatabase management, including schema design, indexing, and optimizationExperience withAPI developmentand integrationAbility to manage and transformraw datato usable formats for analytics and reportingFamiliarity withAgile methodologiesand collaborative development environmentsStrong problem‑solving skills, attention to detail, and ability to providetechnical supportfor data systems Design and develop end-to-end data pipelinesthat support ingestion, transformation, and delivery of structured and unstructured data using tools and frameworks aligned withETL architecturebest practices. Build and maintainETL processesthat ensure data quality, consistency, and performance across multiple environments. Integrate data pipelines withAmazon Web Services (AWS), leveraging services such as S3, Lambda, Glue, and Redshift to enable scalable and secure data processing. Develop and maintainschemas , data dictionaries, and transformation logic to support robustdata architectureand documentation. Manage and monitorproduction datasets, ensuringfault tolerance , redundancy, anddata integrityacross systems. Collaborate with cross‑functional teams to design and launch new data features, including documentation ofdataflows , capabilities, andtechnical supportprocedures. Supportdatabase management and administrationtasks such as performance tuning, indexing, and access control. ApplyAgile software developmentpractices to deliver iterative improvements and respond to evolving data needs. Develop and integrateAPIsto support data access and interoperability across systems. Work withcloud messaging APIsand implementpush notificationmechanisms where applicable. Continuously explore and adopt new tools, technologies, and methods to improvedata engineeringpractices and support mission‑driven outcomes.