Data Engineer

Responsibilities

• Design, develop, and maintain scalable, production-ready data pipelines using Spark, Python, and SQL in a Databricks environment
• Integrate and transform diverse health, financial, and operational datasets into reliable, reusable data products
• Develop data models and analytics datasets that support enterprise reporting and operational decision-making
• Build and maintain API-based integrations for ingesting and exchanging data across systems
• Monitor, troubleshoot, and optimize scheduled workflows and production pipelines for performance, reliability, and scalability
• Implement data validation, quality checks, lineage, and governance practices
• Collaborate with engineers, architects, analysts, and customer stakeholders to translate data needs into technical solutions

Requirements

• 3+ years of data engineering or software engineering experience
• Strong proficiency with Python and SQL
• Experience with Apache Spark or similar distributed frameworks
• Experience working with Databricks or similar modern data platforms
• Experience building production data pipelines and ETL/ELT processes
• Working knowledge of data modeling and transforming raw data into analytics datasets
• Experience integrating or consuming data through REST APIs
• Experience with Git-based development workflows
• U.S. Citizenship required with an active DoD Secret clearance (or higher)

Preferred Qualifications

• AWS cloud experience
• Experience with Palantir Foundry or Advana environments
• Experience working with very large datasets (billions of records)
• Experience with GitLab or CI/CD pipelines
• Experience working with federal health or regulated sensitive data

Benefits

• Flexible PTO plus all Federal holidays off
• Health, dental, and vision insurance plans
• 401k with employer match
• Professional development training and certifications
• Paid cloud developer accounts