Data Architect Senior Staff - Level 5

Lockheed Martin•Fort Worth, TX

2d•Hybrid

About The Position

Designs and implements enterprise‑wide data solutions that define how data is stored, integrated, consumed, and managed across multiple IT systems and business applications. Responsibilities include creating conceptual, logical, and physical data models; architecting end‑to-end data pipelines (ETL/ELT, streaming, SAP/HANA integration); establishing data‑governance and metadata standards; enabling analytics and AI/ML workloads through containerized deployments; and collaborating with business partners to translate requirements into secure, high‑performance data platforms. What’s In It For You: From onsite to remote, we offer flexible work schedules to comprehensive benefits investing in your future and security. Learn more about Lockheed Martin’s comprehensive benefits package here. Do you want to be part of a company culture that empowers employees to think big, lead with a growth mindset, and make the impossible a reality? We provide the resources and give you the flexibility to enable inspiration and focus - if you have the passion and courage to dream big, work hard, and have fun doing what you love then we want to build a better tomorrow with you.

Requirements

Bachelor’s degree in Computer Science, Data Science, Statistics, Engineering, or a related quantitative field (Master’s preferred)
Proven ability to design and deploy enterprise data platforms that integrate SAP/HANA or equivalent and Python‑based pipelines
Strong expertise in SQL with complex query writing and optimization
Hands‑on experience with data‑warehousing concepts (for example; ETL, data modeling, reporting)
Proficiency in Python (or R) for data manipulation and statistical analysis
Ability to obtain and maintain a Secret security clearance; excellent written and verbal communication skills for interfacing with technical and non‑technical stakeholders.

Nice To Haves

Master’s degree in Data Science, Statistics, Computer Science, or a related field
Experience with containerization technologies such as Docker and Kubernetes
Deep knowledge of statistical modeling and machine‑learning techniques
Demonstrated ability to design, develop, and deploy AI‑powered solutions on high‑performance compute infrastructure
Proficiency with data‑visualization tools like Tableau or Power BI
Familiarity with SAP ERP and analytics tools; certifications in cloud data services (e.g., AWS Data Analytics, Google Professional Data Engineer) or equivalent.

Responsibilities

creating conceptual, logical, and physical data models
architecting end‑to-end data pipelines (ETL/ELT, streaming, SAP/HANA integration)
establishing data‑governance and metadata standards
enabling analytics and AI/ML workloads through containerized deployments
collaborating with business partners to translate requirements into secure, high‑performance data platforms