About this role
Google Global Fleet (GGF) is responsible for Alphabet-wide end-to-end demand and capacity planning. Its mission is to reduce waste, increase delivery reliability, and decrease lead time while delivering infrastructure to support ML, workloads, internal partners, and Cloud customers. Avoiding shortages and ensuring maximum agility, efficiency, and velocity is the focus of GGF.
OneSource is a sub-organization in GGF which is responsible for data engineering. The mission of OneSource is to enable highly efficient and reliable fleet resource lifecycle by: building and evolving a unified and extensible data system; establishing a canonical source of truth for timely and high-quality data that enables GGF systems to deliver its mission.
As a Principal Software Engineer for Google Global Fleet-OneSource, you will pioneer the technological vision for a critical mandate. You will discover the defining technologies and forge the architectural path for data engineering empowering our ability to cater to the largest, most demanding internal and external AI/ML customers with a data framework for unmatched performance and reliable capacity planning.
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: $307000 - $427000 (USD) + 30% bonus target + equity + benefits
Learn more about benefits at Google (https://www.google.com/about/careers/applications/benefits/).
Minimum qualifications:
- Bachelor's degree in Computer Science or similar technical field, or equivalent practical experience.
- 15 years of experience as a software engineer.
- Experience creating a shared vision, coupled with clear communication and a leadership approach.
Preferred qualifications:
- Master's degree or Ph.D. in Computer Science, a field related in Data Engineering, or Data Analytics.
- Deep understanding of the latest AI and ML capabilities.
- Demonstrated ability to influence and lead without direct authority, building strong relationships and driving alignment across teams.
- Ability to upskill teams and integrate AI-driven solutions to improve large-scale systems such as reducing capacity delivery lead times, improve testing coverage, and streamline both software development and network design processes.
- Proven track record of successfully leading and delivering large-scale, complex systems.
- Lead the solution architecture for information engineering consisting of data lake, semantics and ontology that can scale and support a multi-year engineering roadmap to deliver 100x more capacity for explosive AI/ML demand growth. This includes data engineering for AI agent consumption.
- Leverage deep technical knowledge across the full software stack—spanning backend, front end and data engineering.
- Partner across sub orgs within AI & Infrastructure (AI2) and Google Global Infrastructure (GGI) to define system data flows and interfaces to solve supply demand matching problems.
- Ensure the design and implementation guidance to the engineering team rectifies the inefficiency, if any, in the existing workflows and data engineering pioneers the redesign of workflows/processes to uplift the speed of delivery for the next decade or so.