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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer Sr Staff - Level 5 - **Company:** Lockheed Martin - **Location:** Fort Worth, TX, United States - **Experience:** Expert - **Salary:** $129,000.0 - $239,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Systems Engineering, Architectural Patterns, Authentication Protocols, Cloud Computing, Databases, Data Architecture, Extract Transform Load (ETL), Data Systems, Data Virtualization, Decision Support Systems, Metadata, Software Engineering, Enterprise Data Management, Data Processing, Togaf, Data Management, Data Objects, Physical Data Models, Data Pipelines, Databricks - **Published:** September 10, 2026 - **Apply:** https://dejobs.org/x/x/3AC9175884EC4C1CA2B81C38BA0A4862/job/ ## About the Role * Bachelor's degree in a related technical discipline plus 14+ years in data architecture or enterprise data management * Demonstrated ownership of enterprise or functional data-architecture strategy, reference architectures, and common data models * Advanced conceptual, logical, and physical data modeling for complex, cross-organizational domains * Demonstrated authorship of governance and architecture artifacts - standards, models, architectural decision records - and experience presenting to senior governance bodies * Ability to obtain and maintain a U.S. DoD Secret clearance (U.S. citizenship required) Desired Skills * Databricks (Unity Catalog, Delta, Lakehouse patterns) * Metadata, lineage, glossary, and data-product certification design * Common data modeling and semantic interoperability across federated organizations * Familiarity with controlled command-media authoring in a regulated enterprise * Quality data-model domain experience (nonconformance, corrective action, assessment, inspection) * Relevant certifications (e.g., CDMP, TOGAF, Databricks Data Engineer, Security+) ## Description Lockheed Martin Aeronautics Quality & Mission Success (Q&MS) is seeking a Senior Staff Data Engineer to lead the architecting and implementation of the Q&MS data system and its supporting data-management plan. Reporting into Quality Performance Management and aligned to the Q&MS Digital Transformation Director, the role establishes the reference architecture, common data models, and governance patterns that consolidate fragmented Q&MS data into governed, value-creating data products fit for reporting, decision support, and approved AI uses. The architect works across a federated operating model spanning multiple participating organizations, replacing fragmented pipelines and definitions with a coherent, measurable data system, and interfaces with the Aeronautics data office, 1LMX, IT, and other intra- and extra-functional teams., * Establish and maintain the target-state reference architecture across the data-system lifecycle, along with the current-to-target transition architecture. * Author and maintain common and canonical data models; reconcile them with applicable enterprise and business-unit models to enable semantic interoperability and shared reuse. * Own the multi-year data-architecture roadmap that feeds the annual data portfolio plan; sequence capability increments, dependencies, and shared-capability alternatives before dev/test/build sequences. * Author functional data-architecture command media aligned to applicable enterprise data-management, governance, stewardship, and data-quality direction; prepare architecture-decision content for senior functional leadership and higher-tier governance bodies. * Define architectural patterns and certification criteria for governed data products, pipelines, and interfaces so participating intra-Q&MS organizations can adopt shared capabilities without divergent localized implementations. * Translate organizational data-management maturity gaps into architectural investments carried in the Q&MS data-system roadmap. * Advise on governance approach for AI enablement - traceability, lineage, and fitness-for-use for approved AI agentic use cases. * Serve as the architecture interface to the enterprise data office, corporate IT, and corporate data and AI enablement organizations; elevate matters beyond functional authority through the applicable interface. * Mentor Staff and Senior data engineers, modelers, and technical stewards across participating organizations. Delivers full-stack data solutions across the entire data processing pipeline. This relies on systems engineering principles to design and implement solutions that span the data lifecycle to: collect, ingest, process, store, persist, access, and deliver data at scale and at speed. It includes knowledge of local, distributed, and cloud-based technologies; data virtualization and smart caching; and all security and authentication mechanisms required to protect the data.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 ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)