Data Engineer at SAIC

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Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

0.0

Posted On

13 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Pipelines, Data Formats, Automation, Data Orchestration, Data Stores, Real-Time Indexing, Data Transfers, Data Models, Python, NLP, Regular Expressions, ETL, Schema Evolution, Cross-Domain Solutions, Data Governance, Data Query Optimization

Industry

Defense and Space Manufacturing

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. Responsibilities: Build and optimize robust data pipelines: ingestion, transformation, storage, and governance. Convert between tactical data formats, e.g., XML, JSON, GEOJSON, Cursor-on-Target (CoT), JREAP-C, Link-16. Implement automation using CHRON/CRON jobs and data orchestration frameworks (Apache Airflow, Kafka, AWS Step Functions). Architect and maintain scalable data stores (e.g., Apache Iceberg, Elasticsearch) with schema evolution and deduplication. Enable real-time data indexing and fast query performance. Implement MIL-STD-6016 (Link-16) and MIL-STD-3011 (JREAP) message handling. Support integration or development of Cross-Domain Solutions (CDS) for secure, policy-based data transfers. Present complex data flows and technical insights effectively to leadership and stakeholders using clear data models and visual aids. 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 9 years' experience working as a business analyst, data analyst, data scientist, data engineer, database administrator, geospatial analyst, geospatial engineer, machine learning engineer, or software engineer. Hands on Keyboard- Developer Skillsets. Fluency in Python, can code without Modern libraries. Experience in format conversions with some of the following: XML, JREAP-C, COT (cursor-on-target), JSON, GEO JSON, UMF/UHR, text link-16, Tapil-J, and other Tactical Data Links. Experience in natural language parsing (NLP) and using regular expressions, RegEx. Experience implementing CHRON/CRON jobs. Experience in data pipeline orchestration, ETL, orchestration tools (e.g., Kafka, Apache Airflow, AWS Step Functions). Focused experience implementing and monitoring data stores i.e. (Apache Iceberg, elastic search, data lake management). Experience with schema evolution, dataflow and governance. Experience with real-time search and analytics engines for indexing and querying semi-structured data. Focused experience optimizing data store queries for speed and deduplication. Direct experience implementing MIL-STD-6016 and MIL-STD-3011 . Can translate data between source and destination schemas. Data modeling and PowerPoint presentations for leadership and stakeholder presentations. Experience working with or developing Cross Domain Solutions (CDS) systems. 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.

Responsibilities

The Data Engineer will build and optimize robust data pipelines and convert between various tactical data formats. They will also implement automation and maintain scalable data stores to support the Navy-led network-centric initiative.