Data Engineer - Level 4

Lockheed Martin is a leader in aerospace and defense, and they are seeking a Level 4 Data Engineer to support the Enterprise Performance Intelligence Team. In this role, you will design and implement data solutions that span the entire data lifecycle, ensuring the effective processing and delivery of data at scale.

Responsibilities:

• Build data pipelines that clean, transform, and aggregate unorganized data into databases or data sources that are ready for analysis
• Design and implement data solutions by defining functional capabilities, security, back-up, and recovery specifications
• Work through all stages of a data solution lifecycle, e.g., analyze / profile data, create conceptual, logical and physical data model designs, architect and design ETL, reporting and analytics
• Maintain data systems performance by identifying and resolving production and application development problems
• Calculating optimum values for parameters; evaluating, integrating, and installing new releases
• Define standards, best practices, and certification processes for data objects

Requirements:

• Bachelor's degree in Computer Science, Information Technology, or related field
• 5+ years of experience in data engineering, software development, or a related field
• Experience programming in languages such as Python, MS SQL, JavaScript and HTML
• Experience building and maintaining REACT webapps using: Javascript, CSS, and JSX
• Experience designing and maintaining NodeJS, RESTful APIs
• Develop and maintain Gitlab/CICD pipelines using solutions such as: Docker, Harbor, and OpenShift deployments
• Due to program requirements, U.S. citizenship is required
• Experience with Full Stack data pipeline architecture and security requirements
• Familiarity with Artificial Intelligence, Machine Learning, and UI/UX experience
• Familiarity with agile development methodologies and version control systems
• Familiarity with LangChain, LangGraph, Ontologies, and Graph Database
• Familiarity with AI Orchestrators, Agentic Agents, RAG, Optimized Token Chunking Strategies