Lead Data Engineer

1. Job Overview

Lockheed Martin — Data & AI Enablement organization

Join Lockheed Martin’s Data & AI Enablement organization and accelerate the company’s AI transformation. As a lead data engineer, you will design, build, and productize data assets that power AI agents, analytics, and enterprise applications across the Enterprise Data Ecosystem (EDE). In addition, you will lead the development, governance, and expansion of the enterprise ontology, ensuring consistent semantic definitions and relationships across all data products.

Role purpose: Lead the design, development, governance, productization, and operationalization of enterprise-scale data models, pipelines, and ontology assets to support AI agents, analytics, and enterprise applications.

2. Key Responsibilities

• Lead end‑to‑end development of corporate and functional data models and pipelines – from raw data ingestion from source systems to gold-layer entities - so that they can be productized as certified data products.
• Define product vision, roadmap, SLAs, usage metrics, and continuous‑improvement cycles for all data assets.
• Develop, maintain, and govern the Enterprise ontology (concepts, relationships, taxonomies) and deploy it for use by AI agents and analytics applications across the corporation.
• Ensure data models deliver clean, well‑documented feature sets for machine‑learning pipelines; work with data scientists to embed model‑ready attributes (feature stores, lineage metadata).
• Implement security, governance, and compliance (encryption, fine‑grained access, data lineage) via Unity Catalog and cloud IAM
• Collaborate with team architects to validate designs.
• Optimize Databricks performance with auto‑scaling, caching, and Delta Lake tuning.
• Establish standards, best practices, and certification processes for data products and ontology assets.
• Mentor and develop engineering talent through code reviews, hands‑on workshops, paired‑programming, and defined growth paths/competency matrices.
• Advise on the technology stack used in team operations.

3. Required Qualifications

• Bachelor’s (or higher) in Computer Science, Systems Engineering, Information Management, or a related field.
• Must be a US citizen.

4. Required Skills

• 7+ years of large-scale data architecture/engineering experience, with at least 4 years focused on productizing data assets for enterprise consumption.
• Significant experience developing 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.

5. Preferred Qualifications

• 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.

6. Experience Requirements

• Experience level: Experienced Professional
• Stated experience range: 7+ years of large-scale data architecture/engineering experience, with at least 4 years focused on productizing data assets for enterprise consumption.

7. Additional Job Information

• Employment type: Full-time
• Work mode: Flexible work arrangements noted (e.g., 4x10) — source does not explicitly state Remote/Hybrid/On-site as a single value.
• Notice period: Not specified in the source content.
• Locations provided by employer: San Francisco, CA; San Francisco County, CA; California, United States.
• Clearance: None required prior to start; Final Clearance: None.
• Pay transparency: Full-time salary ranges listed by GeoZone in the source requisition.
• Benefits (as listed in source): Medical, Dental, Vision, Flexible work arrangements and schedules (e.g., 4x10), 401(k) match, Paid time off, Holidays, Parental Leave, EAP, Flexible Spending Accounts, Education Assistance, Life Insurance, Short-Term Disability, Long-Term Disability. Annual short-term and/or long-term incentive compensation programs may be offered depending on the position.
• How to apply: Refer to the job posting or the requisition page for application (see the job posting URL provided during application sourcing).