Data Engineer (Op AI) Job Listing at SAIC in San Diego, CA (Job ID 2512350)

Description

Description

SAIC is seeking a TS/SCI cleared Senior Data Engineer in support of NAVWAR's Naval Operational Architecture (NOA) program in San Diego, CA. The Data Engineer will to 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.

 

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

Citizenship and Clearance Requirement:

• U.S. Citizenship required.
• Active TS/SCI security clearance required.

Education and Certification Requirements:

• Bachelor's degree in Data Science, Computer Science, Engineering, or related STEM field and nine (9) years or Masters and seven (7) years or more of experience.

Required Skills and Experience:

• At least 3 years of 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.
• Previous experience with government agencies or military organizations.
• 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: 

• Familiarity with DoD data architecture principles (e.g. DoDAF, CADM).
• Experience with DataOps or similar mission-critical pipeline automation (e.g., deduplication, schema normalization).
• Any experience leveraging universal data distribution architectures within DOD operations.

Target salary range: $120,001 - $160,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.

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