Data Engineer

Talentify; Washington (District of Columbia); On-site; USD 120,000 - 180,000; Full time

Job summary

BigBear.ai is seeking a skilled Data Engineer to join the Data Architecture & Engineering team in the United States. You will design and build scalable, secure data pipelines that transform raw data into actionable insights, across cloud environments and databases.

Expect to work on ETL development, AWS services, and end-to-end data processing in an Agile setting. You will maintain data schemas and dictionaries, ensure data quality, and collaborate to launch new data features.

Qualifications

• 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 AWS and cloud-based data integration.
• Strong experience with ETL architecture, data pipeline development, and end-to-end data processing.
• Solid understanding of database management, including schema design, indexing, and optimization.
• Experience with API development and integration.
• Ability to manage and transform raw data into usable formats for analytics and reporting.
• Familiarity with Agile methodologies and collaborative development environments.
• Strong problem-solving skills, attention to detail, and ability to provide technical support for data systems.

Responsibilities

• Design and develop end-to-end data pipelines that support ingestion, transformation, and delivery of structured and unstructured data using ETL best practices.
• Build and maintain ETL processes that ensure data quality, consistency, and performance across environments.
• Integrate data pipelines with AWS services (S3, Lambda, Glue, Redshift) for scalable data processing.
• Develop and maintain schemas, data dictionaries, and transformation logic for robust data architecture.
• 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 and document dataflows and capabilities.
• Support database management tasks such as performance tuning, indexing, and access control.
• Apply Agile practices to deliver iterative improvements and meet evolving data needs.
• Develop and integrate APIs to support data access and interoperability across systems.

Skills

TS-SCI clearance

Data engineering

ETL development

Database administration

API development

Agile methodologies

Education

Bachelor’s degree in computer science, Engineering, Information Systems, or related field

Tools

AWS

S3

Lambda

Glue

Redshift

Job description

Open — BigBear has a posting for this job. Posted 23 Aug 2026.

This posting

Opens careers.bigbear.ai. Talentify has not checked who owns that address. You apply there — Talentify never asks for an account or a CV.

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About this job

Residency

All applicants must reside in the United States at the time of application.

Overview

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.

What you will do

• 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.

What you need to have

• 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
• Solid understanding of database management, including schema design, indexing, and optimization
• Experience with API development and integration
• Ability to manage and transform raw data into usable formats for analytics and reporting
• Familiarity with Agile methodologies and collaborative development environments
• Strong problem‑solving skills, attention to detail, and ability to provide technical support for data systems

What we'd like you to have

• Experience with cloud messaging APIs and push notification systems
• Hands‑on experience with database administration and performance tuning
• Keen interest in learning and applying the latest data tools and technologies to solve real‑world problems
• Experience supporting technical support functions related to data infrastructure
• Familiarity with national security or 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.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.

• 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
• Solid understanding of database management, including schema design, indexing, and optimization
• Experience with API development and integration
• Ability to manage and transform raw data to usable formats for analytics and reporting
• Familiarity with Agile methodologies and collaborative development environments
• Strong problem‑solving skills, attention to detail, and ability to provide technical support for data systems
• 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.