AI Data Architect Senior Staff

Lockheed Martin•Orlando, CO

1d•Remote

About The Position

As a Senior Staff AI Data Architect, you will be an instrumental member of the Data & AI Enablement organization supporting LM Space Systems to effect ground-breaking changes that enables advanced AI/ML capabilities, define new solutions, redefine older architectures, and shape ontology-driven frameworks. Providing technical leadership and expertise in the design, implementation, and optimization of Data Management & Governance capabilities from the data collection to the data consumers. Lead LM Space's Master Data Management (MDM) strategy and architecture, defining standards, patterns, and governance models that ensure consistent, high-quality master data across business domains and systems with AI/ML enablement. Partner across business areas and Enterprise with data engineering, analytics, and governance teams to design and implement scalable and secure data architectures enabling ontology-driven data models. Partner closely with business stakeholders, systems owners, and enterprise teams to translate business capabilities and data requirements into MDM solutions that advance AI/ML enablement, operational efficiency, analytics, and decision-making. Drive master data integration, data quality, and data lifecycle management, including source system alignment, golden record design, metadata management, and stewardship enablement. Provide technical and program management leadership with influence, guiding cross-functional teams, vendors, and integrators while mentoring junior architects and shaping enterprise data architecture best practices.

Requirements

Demonstrated experience in designing and implementing Master Data Management framework with AI/ML enablement in Aerospace industry, including ontology domain modeling and data quality management across multiple source systems.
Strong expertise in enterprise data architecture and data modeling, including conceptual, logical, and physical models, and experience working within complex, federated data environments.
Hands-on experience collaborating with Aerospace business stakeholders and system owners, translating business requirements into scalable AI/ML enabled data solutions and influencing decisions across organizational boundaries.
Experience working in large, complex aerospace/defense organizations with formal data governance, security, and compliance requirements, and the ability to navigate ambiguity and drive alignment.
Excellent executive-level communication and storytelling skills, capable of articulating complex data concepts, tradeoffs, and value in a clear, business-focused manner.

Nice To Haves

Deep knowledge of Master Data Management platforms and patterns (e.g., CP4D, SAP MDG) including reference data management
Strong data governance and stewardship enablement skills, with experience partnering with data owners, stewards, and governance bodies to operationalize policies, standards, and accountability.
Ability to influence and lead across matrixed organizations, aligning business, IT, and enterprise stakeholders without direct authority through clear communication and trusted relationships.
Experience designing and implementing data integration and interoperability solutions, leveraging APIs, AI/ML, ontologies, event-driven architectures, and modern data platforms (cloud, hybrid, on-prem)
Experience with SAP S4/HANA (ERP), PTC Windchill (PLM), Siemens Team Center (PLM), Dassault 3D Experience (PLM) or VE-CAMS & Apriso (MES)
Experience with data virtualization (Tibco), reporting tools (Tableau, Webi), data storage (DB2, HANA, Oracle), Cloud and on-prem platforms, and Extract Transform Load processes (SAP Data Services), and CP4D data management platform
Experience with data catalog and business glossary platforms
Experience working in Aerospace industry

Responsibilities

Lead LM Space's Master Data Management (MDM) strategy and architecture, defining standards, patterns, and governance models that ensure consistent, high-quality master data across business domains and systems with AI/ML enablement.
Partner across business areas and Enterprise with data engineering, analytics, and governance teams to design and implement scalable and secure data architectures enabling ontology-driven data models.
Partner closely with business stakeholders, systems owners, and enterprise teams to translate business capabilities and data requirements into MDM solutions that advance AI/ML enablement, operational efficiency, analytics, and decision-making.
Drive master data integration, data quality, and data lifecycle management, including source system alignment, golden record design, metadata management, and stewardship enablement.
Provide technical and program management leadership with influence, guiding cross-functional teams, vendors, and integrators while mentoring junior architects and shaping enterprise data architecture best practices.