Data Engineer - Senior - level

Data Engineer

The Data Engineer supports USINDOPACOM J2 by designing, developing, and optimizing data management systems that enable advanced intelligence analysis across the Indo-Pacific theater. This senior-level role focuses on building scalable data architectures, integrating structured and unstructured data sources, enhancing data accessibility, and improving analytic throughput for all-source intelligence missions. The ideal candidate has deep expertise in database engineering, ETL pipelines, data modeling, and analytic-enabling technologies, along with experience collaborating across the Intelligence Community (IC), academia, and partner organizations.

Responsibilities

Data Architecture, Engineering & Optimization

• Designs, implements, and operates data management systems tailored to intelligence mission needs.
• Develops data storage, access, integration, and management strategies across diverse data regimes and digital systems.
• Works closely with analysts and data users to design optimal data architectures, schemas, and pipelines.
• Plans and optimizes data throughput, indexing, and query performance to ensure responsiveness and scalability.
• Participates in selecting and configuring backend database technologies—including SQL, NoSQL, and high-performance computing (HPC) platforms.

Large-Scale Data Processing & Analytics Support

• Develops, maintains, and analyzes large structured and unstructured datasets to support all-source intelligence production.
• Identifies critical factors, trends, vulnerabilities, and opportunities within datasets that advance analytic understanding and situational awareness.
• Enhances data quality, accessibility, and analytic consistency across the intelligence enterprise.

Modeling, Data Mining & Predictive Analytics

• Designs and builds new processes, models, and data-mining workflows to improve analytic output and intelligence production.
• Develops predictive capabilities and enhances search quality using advanced data-engineering techniques.
• Creates prototypes, algorithms, and custom analytical tools to address division priorities and theater intelligence requirements.

Prototype Development & Custom Solutions

• Conducts tailored data analysis and develops algorithmic solutions to support operational and strategic intelligence needs.
• Generates custom tools, processes, or data models as required to address emerging mission challenges.

Collaboration & Community Integration

• Collaborates extensively with all-source analysts, data scientists, and IC partners to support shared analytic efforts.
• Participates in meetings, working groups, and collaborative forums to synchronize data efforts across the enterprise.
• Ensures alignment with theater-wide data strategies and supports integration of new analytic workflows.

Data Lake Management & Enterprise Integration

• Maintains and expands the USINDOPACOM J2 "data lake," ensuring it remains a robust, accessible repository for multi-domain intelligence data.
• Coordinates with U.S. interagency partners, international allies, academic institutions, and research organizations to incorporate new data sources.
• Ensures datasets are ingested, structured, and accessible for daily analytic use and enterprise-wide operations.

Qualifications

Senior-level experience in data engineering, data architecture, or database development supporting DoD or IC missions. Expertise in SQL/NoSQL systems, ETL pipelines, big-data frameworks, and backend optimization. Proficiency in programming languages commonly used for data engineering (e.g., Python, R, Java, Scala). Experience working with structured and unstructured datasets and developing predictive or analytic-enabling processes. Strong communication skills and ability to collaborate with analysts and mission partners across the IC. Demonstrated ability to design scalable, secure data architectures for mission-critical environments.

Preferred Qualifications

• Experience supporting USINDOPACOM or a Geographic Combatant Command.
• Familiarity with data science, AI/ML pipelines, and analytic automation.
• Experience integrating partner and allied data into enterprise architectures.
• Background in computer science, engineering, information systems, or related technical fields.