Technical Program Manager II, NPI Data Center Design, Cloud Supply Chain
GoogleBridgeport, Alabama
Full-time
Salary
$138k–$197k/ annually
Free account to apply · application completed on Google
Salary
$138k–$197k/ annually
Free account to apply · application completed on Google
MINIMUM QUALIFICATIONS:
* Bachelor's degree in a technical field, or equivalent practical experience.
* 2 years of experience in program management.
* Experience with data center infrastructure like power, networking, and
cooling.
* Experiencing managing the hardware New Product Introduction (NPI) life-cycle.
PREFERRED QUALIFICATIONS:
* 2 years of experience managing cross-functional or cross-team projects.
* Experience with New Product Introduction (NPI) process and Product life-cycle
(PLC) as related to hardware products for machine learning and
high-performance computing.
* Experience managing data center constraints with the knowledge of data center
physical layouts, infrastructure, and standards (power, space, cooling,
operations and network).
* Experience with data center, networking and machine deployments, including
in-depth understanding of deployment process and the ability to drive tools
and automation for continuous process improvement.
* Excellent program management skills with the ability to co-ordinate
deployments and roadmaps across multiple stakeholders.
ABOUT THE JOB:
A problem isn’t truly solved until it’s solved for all. That’s why Googlers
build products that help create opportunities for everyone, whether down the
street or across the globe. As a Technical Program Manager at Google, you’ll use
your technical expertise to lead complex, multi-disciplinary projects from start
to finish. You’ll work with stakeholders to plan requirements, identify risks,
manage project schedules, and communicate clearly with cross-functional partners
across the company. You're equally comfortable explaining your team's analyses
and recommendations to executives as you are discussing the technical tradeoffs
in product development with engineers.
As a part of the team, you will be focused on aligning new products and
technical infrastructure interface roadmaps to enable fast, predictable and
optimized deployment of heterogeneous machines for all product areas across
Google’s Data Center and third-party fleet. You will ensure that every machine
tech is optimally deployable across the fleet with touchless space, power,
network, and cooling planning and accomplish this by influencing products
(optimize utilization of tech infrastructure), influencing ecosystems (tools and
processes for predictability), and shaping infrastructure (new server floor
designs).
Google Cloud accelerates every organization’s ability to digitally transform its
business and industry. We deliver enterprise-grade solutions that leverage
Google’s cutting-edge technology, and tools that help developers build more
sustainably. Customers in more than 200 countries and territories turn to Google
Cloud as their trusted partner to enable growth and solve their most critical
business problems.
Individual pay is determined by factors including job-related skills,
experience, and relevant education or training.
US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google
[https://www.google.com/about/careers/applications/benefits/].
RESPONSIBILITIES:
* Manage project delivery while addressing data center constraints (e.g.,
power, space, cooling, operations, and network) in colocation data center
deployments.
* Design and manage physical layouts, standards, and tooling requirements
including assessment of deployment impact and feasibility of NPIs for
planning and delivery.
* Build and support relationships between cross-functional teams, track
deployment workflows with partner teams, and raise issues to ensure on-time
follow-through.
* Influence the development of new products (NPI) and colocation server floor
design decisions, focused particularly on upcoming fleetwide transitions in
the ML and accelerators space.
* Drive the development of new tools and decision-making frameworks for
optimizing fleet life-cycle.
