LMI is hiring a Senior Data Engineer to turn fragmented customer data into dependable inputs for national security applications, analytics, and AI. You will build pipelines and data models that connect operational systems to usable workflows. You will work with users and engineers to establish what the data means, where it can be trusted, and how it should be accessed.

You will join a multidisciplinary team within LMI's National Security organization. Work spans technical discovery, rapid prototypes, and selected deployments through initial operational use. The team develops reusable capabilities and transfers them to LMI program or product teams for sustained delivery.

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. 

• Investigate source systems and data with mission users. Define the entities, relationships, and quality expectations needed for the application.
• Build ingestion and transformation pipelines for structured data, documents, APIs, and operational records as the use case requires.
• Reconcile inconsistent identifiers and schemas, model useful relationships, and document definitions and assumptions.
• Implement quality checks, lineage, freshness monitoring, and access controls so users can understand and trust the data.
• Build pipelines that can be tested, monitored, rerun, and recovered safely when sources or requirements change.
• Partner with software and AI engineers to serve reliable application data and prepare information for retrieval and analysis.
• Support initial deployment, resolve data failures, and transfer pipelines, documentation, and operating procedures to the sustaining team.

Required Qualifications

• Strong SQL and Python skills, with production ownership of ingestion, transformation, and relational data modeling.
• Experience turning inconsistent source data into maintained datasets or data products used by applications or decision-makers.
• Experience with a production orchestration and transformation stack such as Airflow or Dagster and dbt or SQLMesh, or comparable tools.
• Experience with schema changes, data quality testing, lineage, permissions, and diagnosis of failed or incomplete pipelines.
• Software engineering practices for data, including version control, automated tests, CI/CD, and reproducible deployment.
• Ability to explain data definitions and limitations, work through ambiguous requirements, and collaborate with application engineers and users.
• Demonstrated use of AI coding tools or agents, with independent review, testing, and security checks of generated code.
• Travel up to 50% for user engagement, deployment support, and forward deployed delivery.
• Active Secret Clearance Required. 

Preferred Qualifications

• Experience with Palantir Foundry pipelines and ontology development, Databricks, or comparable enterprise data platforms.
• Experience with Spark or PySpark, event streaming, document ingestion, entity resolution, or semantic modeling.
• Experience with cloud data services, object storage, and containerized workloads in AWS, Azure, or Google Cloud.
• Experience with defense, intelligence, logistics, manufacturing, supply chain, workforce, or autonomy data and the controls governing its use.
• An active security clearance.

The target salary range for this position is $130,000-$190,000. 

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.