Data Operations Technical Lead (SOCOM)

Overview 

Data Systems Analysts, Inc. (DSA) is seeking a Data Operations Technical Lead to support U.S. Special Operations Command (SOCOM) in building and sustaining enterprise data infrastructure that enables analytics and AI capabilities across the SOF enterprise. 

This role serves as the senior technical authority for data engineering, integration, and data operations activities across the program. The Data Operations Technical Lead will be responsible for ensuring data is accessible, reliable, scalable, and aligned to mission needs across distributed and classified environments.  This role requires a forward leaning technical leader who can apply emerging data engineering and AI enabling technologies to deliver innovative, mission driven solutions

 Location 

Tampa, FL (MacDill AFB) 
CONUS and OCONUS travel required  

 Responsibilities 

• Lead the design, development, and sustainment of enterprise data architectures and pipelines that enable large-scale AI/ML model training, experimentation, and deployment across the SOF enterprise 
• Establish and implement enterprise data management frameworks, including data governance, data quality, metadata management, and compliance with SOCOM policies and data strategies 
• Ensure all data systems and capabilities align with SOCOM data strategy principles, enabling data accessibility, interoperability, and mission effectiveness across distributed environments 
• Oversee data ingestion, transformation, storage, and dissemination processes to ensure data is reliable, scalable, and available to analytics, AI, and mission users 
• Design and implement data sharing solutions that enable interoperability across SOF components, mission partners, and enterprise platforms 
• Lead development of ETL processes, APIs, data schemas, and scalable pipeline architectures across cloud, hybrid, and classified environments 
• Guide DevSecOps and CI/CD practices for data and AI platform delivery, enabling automated, secure, and repeatable deployment of data pipelines and supporting infrastructure 
• Manage data engineering and platform integration teams, providing technical leadership, prioritization, and execution oversight across all data operations activities 
• Work directly with SOF data leaders, mission stakeholders, and operational users to translate mission needs into scalable data engineering solutions aligned to operational priorities 
• Lead agile development processes for data engineering and platform delivery, ensuring responsiveness to evolving mission priorities 
• Lead implementation of data-as-a-product practices, including domain ownership models, data product lifecycle management, and scalable data-centric architectures 
• Develop and sustain enterprise data products that enable analytics, AI, and decision support capabilities across the SOF enterprise 
• Provide data governance and management support to SOF data leaders and stakeholders, ensuring alignment with enterprise initiatives 
• Enable real-time and batch data processing capabilities that support operational decision-making in dynamic mission environments 
• Operate across classified, distributed, and resource-constrained environments, ensuring data solutions meet security and mission requirements 
• Engage government stakeholders to communicate data operations status, performance, risks, and technical approaches 

Required Qualifications 

• Active TS/SCI clearance 
• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or related field 
• 8+ years of experience managing digital projects in support of SOF Enterprise customers
• Experience supporting data pipelines and architectures that enable AI/ML workflows, including model training, experimentation, or deployment in production environments
• Experience leading data engineering or data operations teams in program environments 
• Experience translating digital support requests into actionable data engineering and platform development tasks 
• Experience building and delivering enterprise-scale data pipelines and integration architectures (ETL, streaming, or batch) 
• Experience with data governance, data quality, and metadata management 
• Strong experience with Python and SQL 
• Experience with data orchestration and pipeline tools (e.g., Airflow, NiFi, Spark, Kafka) 
• Experience designing and operating distributed, cloud or hybrid data architectures across cla