Minimum qualifications:
- Bachelor's degree in Electrical Engineering, Process Engineering, Manufacturing Engineering, or equivalent practical experience.
- 8 years of experience in manufacturing, supply chain, data center operations, or related field.
- 2 years of experience managing projects with team members from different organizations.
- 1 year of experience using SQL or another scripting language to find and summarize data.
- Experience leading technical teams through assessments of tradeoffs.
- Experience creating and presenting summaries of technical content to senior leaders.
- Experience creating data-based reporting and visualizations.
- Experience writing User Guides or Business Requirements documents.
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About the job
Google's custom-designed equipment makes up one of the largest and most powerful computing infrastructures in the world. The Manufacturing Operations team is responsible for providing the manufacturing capability to deliver this state-of-the-art physical infrastructure. As a Manufacturing Engineer, you evaluate the product designs and create the processes, tools and procedures behind Google's powerful search technology. When vendors build parts for our infrastructure, you're right there alongside ensuring manufacturing processes are repeatable and controlled. You collaborate with Commodity Managers and Design Engineers to determine Google's infrastructure needs and product specifications. Your work ensures the various pieces of Google's infrastructure fit together perfectly and keep our systems humming along smoothly for a seamless user experience.
The Manufacturing Operations team is responsible for providing the manufacturing capability to deliver Google's state-of-the-art physical infrastructure. As part of Technical Operations, the Data and Analytics team is responsible for ensuring stable data feeds from our manufacturing partners and transforming that data to support manufacturing, quality, and data center workflows, reporting, and insights. The team are experts in the manufacturing data ecosystem, and partner with a broad group of stakeholders to create and enable solutions for emerging manufacturing, quality, and data center challenges.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
The US base salary range for this full-time position is $134,000-$198,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
Responsibilities
- Own manufacturing partner adoption of Google data standards. Set the vision, priorities, and governance structure for vendor teams to: create clear documentation, lead partners through onboarding, and perform data validation and track partner performance against the standards.
- Be an expert in Google's manufacturing data systems, understand as-is system dependencies and how they impact Google's manufacturing and data center workflows. Identify new needs and develop new approaches, by partnering with other systems experts to design and improve systems and tools.
- Utilize technical leadership and judgment to guide cross-functional teams through assessments of capabilities, gaps, and options/trade-offs. Communicate recommendations and risks to senior leadership and broader teams.
- Understand and communicate emerging issues in manufacturing and data center workflows by querying and summarizing findings from a variety of sources.