Lead Data Architect -Prem AI- Analytics Core

Job Description

The Lead Data Engineer / Data Architect will spearhead the creation of our next-generation “Analytics Core” within a closed, classified, on-premises environment. This mission-critical project will unify our 30-year legacy archive of diverse data—including reports, sensor data, imagery, and heavily geospatial intelligence—into a single, query-able, and AI-ready ecosystem.

Job Description

The Lead Data Engineer / Data Architect will spearhead the creation of our next-generation “Analytics Core” within a closed, classified, on-premises environment. This mission-critical project will unify our 30-year legacy archive of diverse data—including reports, sensor data, imagery, and heavily geospatial intelligence—into a single, query-able, and AI-ready ecosystem.

Because our historical data is highly complex with deep attribution challenges, this is a “roll-up-your-sleeves” role. We expect a balance of approximately 60% hands-on data engineering (ETL pipeline construction, data cleaning, and mapping) and 40% data architecture (strategic design and governance).

As our management team upskills our dedicated in-house staff to execute the broader data migration, this role will act as the technical anchor. The Lead Data Engineer / Data Architect will build strong relationships, set clear technical standards, and seamlessly interface with transitioning staff to ensure the project’s success.

Essential

RESPONSIBILITIES

• Data Architecture & Modeling
• Design the foundational multidimensional data models for complex, multi-modal data.
• Untangle 30 years of complex historical data to resolve attribution issues and establish a clean, authoritative data model.
• Foundational Engineering
• Act as the hands-on technical lead to build initial ETL/ELT pipelines using Python, SQL, and on-premises infrastructure.
• Develop programmatic solutions to clean, parse, and ingest legacy unstructured and structured data.
• Geospatial Integration
• Given that nearly all database records contain coordinate data, lead the integration between our on-premises ESRI portal and the new Analytics Core.
• Ensure spatial data seamlessly aligns with the multidimensional model.
• AI/ML Data Preparation
• Establish standards for feature engineering, ensuring the database architecture is optimized for future Artificial Intelligence and Machine Learning applications within a classified environment.
• Governance & Compliance
• Enforce data governance, metadata tagging, and access control protocols in strict alignment with the DoD Data Strategy and classified network handling requirements.
• Cross-Functional Collaboration & Integration
• While management will handle direct personnel training, you must establish effective working relationships and technical interfaces with our evolving internal team:
• Software Engineers:
  Interface with engineers transitioning into data engineering. Provide clear technical specifications, architectural blueprints, and constructive code reviews as they take over building scalable ETL/ELT pipelines.
• GIS Specialist:
  Collaborate closely to integrate their programmatic GIS outputs into the broader AI-ready database. Bridge the gap between standard data engineering and specialized geospatial analytics.
• Junior Data Manager:
  Partner to operationalize data governance. Define data rules and interface with them as they manage the Data Dictionary, enforce quality control, and properly tag legacy metadata.
• General:
• Work independently and as a team member.
• Lead and mentor less experienced employees.
• Ensures work given and completed is within compliance with processes, standards and policies of the organization.
• Lead projects within department or job functions.
• Lead individual contributors to ensure the work completion is as per set standards and procedures.