Principal Business System Analyst, Engineering Operations

NVIDIA•Us, CA

1d•Onsite

About The Position

NVIDIA is hiring a Principal Business System Analyst for Engineering Operations in Santa Clara to help scale how teams plan, prioritize, and deliver enterprise platforms and AI initiatives. The role partners with engineering leaders to translate strategic priorities into execution plans, improve operating practices, and lead sophisticated programs from planning through launch and adoption. The analyst will coordinate operational planning across engineering teams, strengthen portfolio and delivery practices, and support resource decisions with clear information about priorities, dependencies, risks, and tradeoffs. The role also defines metrics connecting engineering delivery to platform reliability, employee efficiency, and business value, and uses automation and AI to improve operational workflows, reporting, and decision-making.

Requirements

Bachelor’s degree in Engineering, Computer Science, Business, or a related field, or equivalent experience with 15+ years of experience.
Significant experience leading engineering operations, technical programs, or complex enterprise technology portfolios.
Track record of improving planning and execution across multiple engineering teams.
Excellent judgment in prioritization, resource planning, dependency management, and navigating ambitious commitments.
Ability to influence senior collaborators, build alignment, and drive accountability across interpersonal boundaries.
Experience defining meaningful metrics and translating data into recommendations and decisions.
Clear communication, including concise executive reporting and recommendations on risks and tradeoffs.
Technical proficiency across enterprise platforms, software delivery, and AI-enabled experiences.

Responsibilities

Lead operational planning across engineering teams, aligning roadmaps, capacity, and commitments with business priorities.
Establish a consistent cadence for portfolio reviews, delivery tracking, risk management, and leadership updates.
Drive cross-functional execution, resolve dependencies, and ensure clear ownership of achievements and outcomes.
Improve intake and prioritization processes to clarify resource decisions and delivery tradeoffs.
Collaborate with engineering and product leaders to coordinate launch readiness, adoption, and ongoing improvements.
Define metrics that connect engineering delivery to platform reliability, employee efficiency, and business value.
Use automation and AI to improve operational workflows, reporting, and decision-making.
Bring structure to ambiguous initiatives and surface decisions requiring leadership alignment.