Overview
LMI is seeking a Data Engineer to support a U.S. Special Operations Command (SOCOM) mission partner. The Data Engineer will design, secure, and sustain enterprise data pipelines and platforms that convert complex business, operational, and intelligence data into governed, machine-learning-ready formats. Working within a cross-functional data science product team, this position will enable predictive analytics, natural language processing, generative AI, automation, dashboards, and mission applications while advancing shared integration and engineering best practices across AI/ML efforts.
LMI is a new breed of digital solutions provider dedicated to accelerating government impact with innovation and speed. Investing in technology and prototypes ahead of need, LMI brings commercial-grade platforms and mission-ready AI to federal agencies at commercial speed.
Leveraging our mission-ready technology and solutions, proven expertise in federal deployment, and strategic relationships, we enhance outcomes for the government, efficiently and effectively. With a focus on agility and collaboration, LMI serves the defense, space, healthcare, and energy sectors—helping agencies navigate complexity and outpace change. Headquartered in Tysons, Virginia, LMI is committed to delivering impactful results that strengthen missions and drive lasting value.
This position requires an active Secret clearance with the ability to obtain a Top-Secret.
Responsibilities
- Design, build, operate, and maintain reliable data pipelines supporting the ingestion, transformation, integration, and storage of structured and unstructured data from multiple mission and enterprise sources.
- Convert historical and operational data into standardized, traceable, machine-learning-ready formats for predictive analytics, natural language processing, large language model, and application use cases.
- Develop and automate batch and real-time ETL/ELT workflows, data integrations, APIs, and orchestration processes that support repeatable analytics and application functionality.
- Design and optimize relational, non-relational, data lake, warehouse, and lakehouse architectures for performance, scalability, availability, and secure access.
- Implement data profiling, validation, reconciliation, schema management, metadata, lineage, monitoring, and quality controls to ensure data accuracy, consistency, accessibility, and auditability.
- Collaborate with data scientists, AI/ML engineers, software developers, analysts, and mission stakeholders to provide clean and structured datasets for model training, evaluation, deployment, and product sustainment.
- Provide enterprise common support, synchronization, integration, reusable engineering patterns, and best practices across multiple AI/ML-focused teams and data science products.
- Apply access controls, encryption, logging, auditing, and handling measures to protect sensitive government data throughout its lifecycle.
- Monitor and optimize pipelines, troubleshoot integration issues, provide rapid-response support, and maintain technical, security, operational, and knowledge-transfer documentation, including instructional videos, for sustainment and transition.
Qualifications
Required Qualifications
- Bachelor's degree in computer science, data engineering, software engineering, information systems, mathematics, engineering, or a related technical field.
- Five or more years of professional experience designing, developing, deploying, and sustaining data pipelines, data platforms, databases, or enterprise data integrations.
- Demonstrated experience building production ETL/ELT pipelines and automated workflows using modern data integration, orchestration, version-control, testing, and continuous-integration practices.
- Advanced proficiency with Python and SQL, including data transformation, query optimization, scripting, automation, and integration with application or analytical services.
- Strong knowledge of data modeling and database architecture across relational, non-relational, object storage, data warehouse, data lake, or lakehouse technologies.
- Experience implementing data quality, schema management, metadata, lineage, observability, reconciliation, and repeatable error-handling processes for complex multi-source datasets.
- Knowledge of secure data engineering practices, including identity and access management, encryption, logging, auditing, least privilege, and protection of sensitive information.
- Experience producing clear technical documentation, architecture diagrams, interface specifications, operational procedures, and knowledge-transfer materials.
- Ability to work independently in a fast-paced, mission-focused environment while collaborating effectively with data science, AI/ML, software, cybersecurity, governance, and operational teams.
- Active SECRET security clearance.
Desired Qualifications
- Master's degree in computer science, data engineering, software engineering, information systems, engineering, or a related technical field.
- Experience supporting SOCOM, the Department of War, another military headquarters, or a comparable national security mission partner.
- Experience with secure government cloud environments such as AWS GovCloud or Azure Government and with containerized, infrastructure-as-code, or DevSecOps delivery practices.
- Experience with distributed processing, workflow orchestration, streaming, API integration, data catalog, or enterprise data governance technologies.
- Experience engineering data for predictive analytics, natural language processing, generative AI, retrieval-augmented generation, vector search, or large language model applications.
- Familiarity with MLOps, model feature pipelines, production application support, automated monitoring, and the transition and sustainment of operational data products.
Target Salary Range: $101,144 - $174,591
Disclaimer: The salary range displayed represents the typical salary range for this position and is not a guarantee of compensation. Individual salaries are determined by various factors including, but not limited to location, internal equity, business considerations, client contract requirements, and candidate qualifications, such as education, experience, skills, and security clearances.
#LI-SH1
Applicants must meet eligibility requirements for a U.S. Government security clearance. Only US Citizens are eligible for a security clearance. For this position, LMI will only consider applicants with security clearances or applicants who are eligible for security clearances, due to the nature of the work.