Principal Data Engineer/Sr. Principal Data Engineer

Northrop Grumman • Palmdale, CA

1d • $114,000 - $213,400 • Onsite

About The Position

Northrop Grumman Aeronautics Systems is hiring a Principal Data Engineer or Sr. Principal Data Engineer for its Data Science Engineering Team. This on-site role is based in Palmdale, California and supports manufacturing-data solutions in a collaborative environment.

The engineer will establish repositories, data models, and integration patterns for manufacturing data and the technical context needed to support digitized processes. The role defines architecture, processes, and interfaces for engineering and manufacturing teams to provide, validate, relate, and maintain contextual data. It also aligns independently managed data structures and designs resilient pipelines and data services for manufacturing measurement, equipment, sensor, process, product-location, quality, engineering, and enterprise-system data.

The successful candidate will set technical direction for greenfield manufacturing-data solutions and communicate strategy, alternatives, risks, dependencies, and outcomes to senior leaders and technical stakeholders. The position requires the ability to obtain and maintain a U.S. Government Secret or Top-Secret clearance and Program Special access within a reasonable period. Work is on-site and requires at least 10% travel. Candidates must be able to work the listed first- or second-shift schedules, or other schedules as needed; shift times may vary.

Requirements

• Principal level: Bachelor’s degree and 4 years of technical and/or engineering experience, Master’s degree and 3 years of engineering experience, or PhD and 0 years of experience.
• Sr. Principal level: Bachelor’s degree and 8 years of engineering experience, Master’s degree and 6 years of engineering experience, or PhD and 4 years of engineering experience.
• Ability to work first shift (5:00 a.m.–3:30 p.m.), second shift (4:12 p.m.–2:42 a.m.), and/or other schedules; times may vary.
• Advanced experience using SQL, programming or automation, and relational data modeling to deliver production data products, applications, or platforms.
• Experience defining and owning data architecture, including repositories, schemas, interfaces, integration patterns, metadata, lineage, data quality, and maintainability.
• Demonstrated success delivering greenfield data solutions where platforms, standards, requirements, data contracts, or system endpoints were incomplete or did not exist.
• Experience designing pipelines and integration approaches for complex data from multiple independently managed sources.
• Experience establishing technical direction for ambiguous data problems and driving alignment across technical and operational stakeholders.
• Ability to communicate architecture, performance, risks, dependencies, and tradeoffs to senior managers and technical stakeholders.
• Ability to obtain and maintain a U.S. Government Secret or Top-Secret clearance and Program Special access within a reasonable period.
• Ability to work at a workstation on a computer or similar device for up to 10 hours or the duration of a shift; occasional extended standing, bending, and kneeling.
• Ability to travel at least 10%.

Nice To Haves

• STEM degree in a related field.
• Experience establishing data architecture across manufacturing measurement, equipment, sensor, process, product, quality, engineering, program, and enterprise-system domains.
• Experience aligning independently managed structures through authoritative sources, shared identifiers, mappings, semantic models, relationships, stewardship, and traceability.
• Experience designing scalable approaches for high-volume, high-frequency, time-dependent, spatial, or otherwise complex technical data.
• Experience developing data services, APIs, or application interfaces that allow domain teams to provide and maintain contextual data.
• Experience with Python, Microsoft SQL Server, Apache Airflow, Git-based development, automated testing, CI/CD, monitoring, or production operations. Python and Airflow are preferred; comparable programming and orchestration experience is acceptable.
• Experience incorporating relevant information from engineering documents, work instructions, or other unstructured technical sources without making document parsing the primary solution focus.
• Experience leading architecture reviews, mentoring technical contributors, and raising data-engineering maturity across an organization.
• Experience partnering with enterprise organizations while independently defining and advancing local manufacturing-data needs when enterprise support or platforms are immature.
• Active U.S. Government Secret or higher security clearance.

Responsibilities

• Establish repositories, data models, and integration patterns for manufacturing data and the technical context needed to support digitized processes.
• Define the architecture, processes, and interfaces through which engineering and manufacturing teams provide, validate, relate, and maintain contextual data.
• Align adjacent and independently managed data structures through authoritative sources, shared identifiers, mappings, semantics, relationships, and traceability.
• Design resilient pipelines and data services integrating manufacturing measurement, equipment, sensor, process, product-location, quality, engineering, and enterprise-system data.
• Set technical direction for greenfield manufacturing-data solutions and communicate strategy, alternatives, risks, dependencies, and outcomes to senior leaders and technical stakeholders.

Benefits

• Health insurance coverage
• Life insurance
• Disability insurance
• Savings plan
• Company-paid holidays
• Paid time off (PTO) for vacation and/or personal business
• Employees may be eligible for overtime, shift differential, and a discretionary bonus, depending on the position
• Employees in Vice President or Director positions may be eligible for long-term incentives
• Relocation assistance may be available

What This Job Offers

• Job Type: Full-time
• Career Level: Senior