Sr. Systems Data Architect - R10231325-3

Description

Northrop Grumman's Corporate Chief Information & Digital Office (CIDO) is seeking a Senior Staff Systems Data Architect to support the Engineering & Manufacturing Solutions (EMS) organization's Service Line team. This role requires a self‑motivated professional with proven experience collaborating in cross‑functional Integrated Product Teams (IPTs). Candidates who reside near a major Northrop Grumman facility are preferred.

• No relocation assistance available
• No clearance required to start
• Clearance type:
  Secret
• Travel:
  Yes, 10% of the time

• Develop and execute a comprehensive data strategy aligned with the organization’s goals, focusing on digital engineering, digital thread, and advanced analytics across the EMS Service Line.
• Oversee data models, aligning data models across engineering and manufacturing to support user needs and align with other service lines and CIDO.
• Collaborate with engineering and business leaders to align data initiatives with program goals as well as the enterprise data governance team.
• Develop and enable program data risk management processes in concurrence with program risk management.
• Maintain knowledge of current and emerging industry and government trends and technologies in data frameworks, management, and analytics, ensuring proper utilization where applicable.
• Display strong stakeholder management skills, including presenting solutions to senior leadership.
• Drive company‑wide data strategy and innovation, aligning technical goals with business objectives.
• Influence and gain buy‑in from key stakeholders, ensuring alignment and successful project delivery.
• Manage data governance, data security, data modeling, and enterprise architecture frameworks.
• Provide experience in understanding, managing, and integrating business or government program data across a variety of tool sets and data sources.
• Data architecture development with understanding of data lakes, warehouses, and/or streaming platforms.
• Continuous Integration/Continuous Deployment experience with CI/CD tools like Git tailored for data pipelines.
• Cloud expertise experience and/or knowledge in cloud platforms like AWS or Azure.
• Support data integration strategy between pillar systems.

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field with 14 years of experience; or Master’s degree with 12 years of experience; or PhD with 10 years of experience.
• 4+ years of experience in data infrastructure, Dev Ops, and data engineering, with 2+ years in a leadership or senior technical role.
• 3 years of experience architecting and realizing scalable, secure, and cost‑effective network platforms.
• 3 years of demonstrated experience in leading large‑scale projects from conception to deployment, managing multidisciplinary teams, and driving success through strategic vision and strong leadership.

• Master’s degree or Ph.D. in data engineering, data science, computer science, cloud computing, or a related field.
• An active U.S. Government Secret level security clearance (at a minimum), to include a closed investigation date completed within the last 6 years.
• Relevant certifications such as AWS Certified Solutions Architect (Professional), AWS Certified Data Analytics Specialty, Azure Data Engineer Associate, or Google Professional Data Engineer.
• MLOps expertise, observability tools, data versioning, and containerization for deploying data engineering workflows.
• Advanced technical knowledge of data science and data architecture.
• Proven understanding of statistics, structured and unstructured data analysis, predictive modeling techniques and data visualization, as well as a good command of emerging methodologies like artificial intelligence.
• Recognized experience as a thought leader and innovator in the development of new tools, methodologies and problem‑solving approaches.
• Demonstrated experience with integration platforms such as Mule Soft, SAP Process Integration (PI), or equivalent middleware solutions for designing and orchestrating enterprise data flows.
• Proven understanding of data models used by engineering and manufacturing…