Data Engineer (Op AI)

Job ID T2600881
Location San Diego, CA, US
Date Posted 2026-03-05
Category Information Technology
Subcategory Database Engr
Schedule Full-Time
Shift Day Job
Travel No
Minimum Clearance Required Top_Secret
Clearance Level Must Be Able to Obtain TS/SCI
Potential for Remote Work ORA_ON_SITE
Description
SAIC is seeking a Data Engineer in support of NAVWAR’s Naval Operational Architecture (NOA) program in San Diego, CA. The Data Engineer will support a transformational, Navy-led network-centric initiative that converges existing systems, automating the correlation of multiple ISR data streams, dramatically reducing the "sensor-to-shooter" timeline. This is a recently awarded contract, funded for five years.
Work is performed on site in San Diego. SAIC is seeking a Data Engineer in support of NAVWAR’s Naval Operational Architecture (NOA) program in San Diego, CA. The Data Engineer will support a transformational, Navy-led network-centric initiative that converges existing systems, automating the correlation of multiple ISR data streams, dramatically reducing the "sensor-to-shooter" timeline. This is a recently awarded contract, funded for five years.
Work is performed on site in San Diego, CA.
Please view our program page for more information and to view all open positions available https//jobs.saic.com/pages/NOA
Job Duties

Conduct data pre-processing, exploratory data analysis, and data pipeline engineering to ensure performant and high-quality data output.
Conduct thorough testing and validation of data pipelines and analytics to ensure accuracy, reliability, and robustness.
Design or normalize data to common standards to support interoperability and analytical workflows.
Develop and deploy data pipelines and analytics in real-world applications.
Work with multiple data formats, including CSV, JSON, XML, Parquet, and ORC.
Perform exploratory data analysis, algorithm development, and testing.
Deploy, monitor, and improve data pipelines for operational environments.
Implement event streaming pipelines using Apache Kafka, RabbitMQ, or ZeroMQ.
Collaborate with analytics, engineering, and mission teams to ensure effective data integration and output quality.
Stay current with emerging trends in data engineering, distributed systems, and modern data architecture.
Document data processes, pipeline structures, and engineering best practices.
Qualifications
Education and Years of Experience Requirements

Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, Statistics, or a related STEM field and eight (8) years of experience in of AI/ML experience in defense or intelligence environments.
Citizenship And Clearance Requirements

No dual citizenship.
Active Top Secret clearance required; TS SCI clearance preferred.
Required Skills And Experience

Experience as a business analyst, data analyst, data scientist, data engineer, database administrator, geospatial analyst/engineer, machine learning engineer, or software engineer.
Strong programming skills in Python.
Experience designing or normalizing data to common standards.
Experience with data pipeline development and real-world deployment.
Experience with multiple data formats CSV, JSON, XML, Parquet, ORC.
Familiarity with event streaming platforms (Kafka, RabbitMQ, ZeroMQ).
Experience with exploratory data analysis, algorithm development, and testing.
Experience deploying, monitoring, and improving data pipelines.
Strong problem-solving and analytical skills.
Excellent communication skills and ability to work effectively in a collaborative team environment.
Familiarity with data pipeline frameworks and libraries (AirByte, Apache Airflow, dbt, Apache Iceberg, Snowflake).
Experience retrieving and managing GIS data (ArcGIS, PostGIS).
Programming skills in Go or Rust.
Expertise with Elasticsearch, Redis, S3, PostgreSQL, or similar data stores.
Experience with AWS native data services EFS, RDS, S3, SNS, SQS.
Experience with distributed computing and parallel processing (AWS Lambda, DASK, Spark).
Familiarity with cloud platforms (AWS, Azure) and containerization (Docker, Kubernetes).
Understanding of cybersecurity principles in the context of data applications.
Ability to safely carry tools, equipment, and materials aboard ship, including ascending and descending shipboard ladders(stairwells) and navigating confined spaces while maintaining required points of contact. Tools and equipment will weigh no more than 50 lbs.
Ability to perform required work aboard Navy vessels and in shipboard environments, including navigating narrow passageways, ascending, and descending ladders (stairwells), working on elevated platforms, and operating in variable sea conditions.
Ability to perform activities on a reoccurring basis during shipboard operations or testing evolutions.
Ability to comply with Navy safety requirements and wear required personal protective equipment (PPE).
Ability to operate in a DDIL office environment.
Preferred Skills And Experience

Experience with large-scale data architecture across secure DoD or government environments.
Experience supporting NAVWAR, NIWC Pacific, or other Navy programs.
Experience integrating data pipelines into operational mission systems.
Familiarity with ML Ops or data engineering in classified or cross-domain environments.
Target salary range $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.