Data Operations & Engineering Lead for Army Platform

Remote Jobs; Arlington (VA); On-site; USD 99,000 - 225,000; Full time

Job summary

Booz Allen Hamilton is seeking a Data Operations and Engineering Lead to guide a cross-functional team embedded with Army customers. You will oversee end-to-end data operations, ensure data quality and reliability, and drive platform operations to support analytics, research, and AI workloads.

You will work with Army stakeholders to translate mission requirements into engineering tasks, shape the data platform roadmap, and implement metrics for data health and operational performance.

Qualifications

• 8+ years leading data operations or data engineering teams.
• Experience with ETL/ELT, data cleansing, and data orchestration.
• Experience with enterprise data platforms and large analytics ecosystems.
• Knowledge of Agile methodologies in data engineering contexts.
• Ability to work with DoD stakeholders and government programs.

Responsibilities

• Lead a team of data engineers, data operations specialists, and data architects.
• Translate Army mission requirements into actionable engineering tasks.
• Ensure secure, stable data environments for analytics and AI workloads.
• Oversee data quality, pipelines, and platform operations end-to-end.
• Shape roadmap for data integration, quality, lineage, and automation.

Skills

Data ops leadership

ETL/ELT pipelines

Data cleansing

Data orchestration

Enterprise data platforms

Analytics workloads

AI workloads

Agile methodologies

Security/compliance

DoD programs

Team management

Stakeholder engagement

Secret clearance

Education

Bachelor's degree

Job description

Booz Allen Hamilton is seeking a Data Operations and Engineering Lead to guide a cross-functional team embedded with Army customers. You will oversee end-to-end data operations, ensure data quality and reliability, and drive platform operations to support analytics, research, and AI workloads.

You will work with Army stakeholders to translate mission requirements into engineering tasks, shape the data platform roadmap, and implement metrics for data health and operational performance.