Big Data Engineer

SAIC•Chantilly, VA

About The Position

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:

Requirements

Active TS/SCI with CI Polygraph
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

Responsibilities

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