Senior Data Engineer

LMI

. Investigate source systems and data with mission users .

Posted 11/9/2026full-timeRemote • United StatesSenior💰 $130,000 - $190,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in SQL and Python for data ingestion, transformation, and relational modeling, while ensuring data quality and compliance through effective monitoring and documentation practices. Collaborates with engineering teams to deliver reliable data solutions and supports deployment processes in dynamic environments.

Highest-signal resume keywords

Strong SQL SkillsStrong Python SkillsData Quality TestingProduction Orchestration ToolsActive Secret Clearance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data IngestionData TransformationRelational Data ModelingSchema ChangesVersion ControlAutomated TestsCI/CDEntity ResolutionSemantic ModelingDocument Ingestion

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

AirflowDagsterDbtSQLMeshDatabricksAWSAzureGoogle CloudPalantir FoundrySpark

Certifications & Qualifications

Active Security Clearance

Industry Keywords

DefenseIntelligenceLogisticsManufacturingSupply ChainWorkforceAutonomy Data

Tech Stack

Tools & technologies

AirflowAWSAzureCloudPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Investigate source systems and data with mission users
Define entities, relationships, and quality expectations needed for applications
Build ingestion and transformation pipelines for structured data, documents, APIs, and operational records
Reconcile inconsistent identifiers and schemas, model useful relationships, and document definitions and assumptions
Implement quality checks, lineage, freshness monitoring, and access controls
Build pipelines that can be tested, monitored, rerun, and safely recovered
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 sustaining teams

Requirements

What you’ll need

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