Senior Data Engineer - Clearance Required
About The Position
LMI is hiring a Senior Data Engineer to turn fragmented customer data into dependable inputs for national security applications, analytics, and AI. The role builds pipelines and data models that connect operational systems to usable workflows, working with users and engineers to establish data meaning, trustworthiness, and access. The position is part of 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 digital solutions provider serving federal agencies and the defense, space, healthcare, and energy sectors. The position is listed as remote and requires an active Secret clearance, with travel up to 50% for user engagement, deployment support, and forward-deployed delivery.
Requirements
- 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 diagnosing 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, including independent review, testing, and security checks of generated code.
- Ability to travel up to 50% for user engagement, deployment support, and forward-deployed delivery.
- Active Secret clearance required.
Nice To Haves
- 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.
Responsibilities
- Investigate source systems and data with mission users; define the entities, relationships, and quality expectations needed for applications.
- Build ingestion and transformation pipelines for structured data, documents, APIs, and operational records as required by use cases.
- 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 safely recovered when sources or requirements change.
- Partner with software and AI engineers to provide 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.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
