Lead Data Architect

Standard Job Description

Join Lockheed Martin’s Data & AI Enablement organization and accelerate the company’s AI transformation. As a lead data architect, you will drive the creation of logical data models that underpin our next‑generation data products and enterprise ontology. You will partner with Data Product Owners by architecting data models, data pipelines and ontologies, and ensure consistent semantic definitions across the Enterprise Data Ecosystem (EDE). The role operates in a Databricks‑centric environment, integrating source systems such as SAP and Apriso upstream, and powering AI agents and analytics applications downstream. By governing and expanding the semantic layer of the corporate data foundation, you will play a key role in the company’s AI transformation.

Key Responsibilities

• Partner with Data Product Owners to capture business requirements and create robust logical data models.
• Design federated ontologies and knowledge‑graph structures that enrich data products and support AI agents, AI reasoning, and analytics applications.
• Ensure models deliver clean, well‑documented feature sets for machine‑learning pipelines; work with data scientists to embed model‑ready attributes (feature stores, lineage metadata).
• Define logical representations for SAP, Apriso, and other source systems and guide ingestion patterns that preserve semantic integrity.
• Produce architecture artifacts (diagrams, data dictionaries, ontology catalogs) and enforce data‑quality, security, and lineage standards.
• Design data entities in a way so that they can be productized to ensure they meet the requirements of their documented use cases.
• Collaborate with the Lead Data Engineer to validate designs.
• Continuously improve modeling processes, promote ontology reuse, and stay current on semantic‑modeling and Databricks advancements.
• Advise on the technology stack used in team operations.

Basic Qualifications

• Bachelor’s (or higher) in Computer Science, Systems Engineering, Information Management, or a related field.
• 10 + years of large-scale data architecture/engineering experience, with at least 5 years focused on productizing data assets for enterprise consumption.
• Significant experience designing/operationalizing ontologies.
• Demonstrated ability to probe for and understand core customer needs as opposed to surface-level needs.
• Strong programming skills in Python and SQL; proficient with Spark (PySpark/Scala) and deep experience with AI-assisted development.
• Experience with data‑integration/orchestration tools (e.g., NiFi, Airflow) for pipeline development.
• Must be a US Citizen.

Desired Skills

• Experience with Databricks (Delta Lake, Unity Catalog, Jobs/Workflows).
• Experience with federated data models and ontologies.
• Excellent interpersonal and collaboration skills for cross‑functional teamwork and internal‑customer support.
• Master’s degree or advanced technical training (optional).
• Databricks certifications (Data Engineer Associate/Professional) or comparable big‑data credentials.
• Experience developing applications leveraging genAI.