Data Engineer Sr - Level 5

Position: Data Engineer Sr Staff - Level 5
** Standard

Job 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, 1

LMX, IT, and other intra- and extra-functional teams.

** Key Responsibilities*
* + 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  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

** Basic Qualifications*
* + Bachelor's degree in a…