Big Data Engineer

Job ID: T2511987

Location: Chantilly, VA, US

Date Posted: 2026-03-05

Category: Information Technology

Subcategory: Big Data Engineer

Schedule: Full-Time

Shift: Day Job

Travel: No

Minimum Clearance Required: TS.SCI_wPoly

Clearance Level Must Be Able to Obtain: None

Potential for Remote Work: ORA_ON_SITE

Description

SAIC is seeking a Big Data Engineer to join our team of professionals providing technical and program services to the Air Force, Space and Intelligence Business Group (AFSI). SAIC provides research, engineering, design, analysis, acquisition, development, integration, test, and operations support to USG Intelligence Community (IC) and Department of Defense (DoD) customers. We support development and delivery of next generation and generation after next national security systems based on land, at sea, in air, and in space.

The Big Data Engineer will support the NRO’s Advanced Systems and Technology (AS&T) Directorate, which researches and develops the nation’s most advanced technology for space-based Intelligence, Surveillance and Reconnaissance (ISR) systems. This individual will provide comprehensive technical support across multiple domains, with a focus on data architecture, ETL processes, and data storage solutions. This role is integral to enhancing AS&T’s technological capabilities and strategic decision-making processes.

The primary functions of the candidate will include, but are not limited to:

• Designs scalable data architectures, leading ETL processes, and oversees the implementation of data storage solutions to include creating, manipulating, and maintaining large databases

• Support the development, integration, and visualization of advanced analytics tools, ensuring efficient data access and insights generation
• Optimize system performance and scalability, implementing continuous improvement initiatives
• Architect, deploy, and maintain multiple, fast-turnaround capabilities used to perform various highly-visible and high-priority collection efforts
• Strategically apply AI/ML to extract, format, and expose in indexed search tools relevant content such as raw text, tabular (CSV, Parquet, Avro) or nested (JSON, JSONL, XML), and other structured /unstructured data types. Data is expected to be of varying formats, schemas, and structures
• Provide Data Engineering support to include cleaning, modeling, and formatting data of unknown formats
• Move data between different cloud storage environments for critical requests
• Coordinate with multiple entities, including mission partners, to ensure capabilities and deliverables meet defined requirements and tradecraft needs
• Create and maintain collection capabilities and deliverables within the Customer’s Amazon Web Services environment utilizing Customer approved AWS services
• Validate collected data to ensure it meets data format requirements
• Document all source code, including how to execute the code
• Perform operations and maintenance on the collection capabilities and deliverables to adapt to changes in collection target, technologies, data formats, and naming conventions

Qualifications



• Active TS/SCI with CI Polygraph
• Bachelors and fourteen (14) years or more experience; Masters and twelve (12) years or more experience; PhD or JD and nine (9) years or more experience.
• Bachelor's degree in Information Technology, Cybersecurity, Computer Science, Information Systems, Data Science, or Software Engineering and 9 years or more experience; Masters 7 years or more experience
• Demonstrated experience with Python
• Ability to maintain SQL and NO-SQL databases
• Demonstrated experience with Tableau or Salesforce
• Ability to create and manage AWS resources, including provisioning EC2 instances, writing and deploying Lambda functions, creating and writing to S3, and managing authorization appropriately across resources with IAM policies
• One Active Certification: CCISO, CISM, CISSP, GSLC, SSCP, Sec+ or GSEC
• Proven experience optimizing data pipelines, performing large-scale data processing, and ensuring data quality
• Strong knowledge of data warehousing concepts, ETL processes, and distributed computing environments