Lead Partner Data Engineer, YouTube
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience designing data pipelines, and dimensional data modeling for synch and asynch system integration and implementation using internal (e.g., Flume, etc.) and external stacks (e.g., DataFlow, Spark, etc.).
- 5 years of experience coding in one or more programming languages.
- 5 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
- 5 years of experience with statistical methodology and data consumption tools such as business intelligence tools, collabs, jupyter notebooks, Tableau, Power BI, DataStudio, and business intelligence platforms.
Preferred qualifications:
- 3 years of experience developing project plans and delivering projects on time within budget and scope.
- 3 years of experience partnering with and managing stakeholders (e.g., users, partners), and customers.
- Experience with Machine Learning for production workflows.
About the job
gTech’s Product and Tools Operations team (gPTO) leverages deep user, operational, and technical insights to innovate Google's Ads products into customer experiences that are so intuitive (or automated) that they require no support at all. gPTO partners closely with gTech’s Support, Professional Services, Product Management, and Engineering teams to innovate and simplify our Ads products and build the productivity tools ecosystem for gTech users.
The YouTube Measurement Partner Engineering and Operations team plays a crucial role in ensuring YouTube's accurate and fair depiction to the public. We are also vital in supporting critical business decisions within the YouTube Partner Engineering organization. We are accountable for the precision and uniformity of the internal data that feeds into third-party reporting tools. Our team contributes to a range of business intelligence projects, for the YouTube Partner Engineering team. We offer technical support to partners and deliver analytical services to various initiatives.
At YouTube, we believe that everyone deserves to have a voice, and that the world is a better place when we listen, share, and build community through our stories. We work together to give everyone the power to share their story, explore what they love, and connect with one another in the process. Working at the intersection of cutting-edge technology and boundless creativity, we move at the speed of culture with a shared goal to show people the world. We explore new ideas, solve real problems, and have fun — and we do it all together.
The US base salary range for this full-time position is $150,000-$220,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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
- Serve as the AMER Tech Lead for Measurement Partner Engineering, collaborating with cross-functional and cross-product teams (e.g., YouTube, Google Ads) on core measurement platforms (Audience Measurement Platform and Relaylog).
- Drive the technical design and implementation of critical audience claims infrastructure used to verify and attribute viewership data.
- Oversee the technical strategy and execution for bespoke first-party (1P) and third-party (3P) audience measurement initiatives.
- Manage the research, implementation, and production deployment of Generative AI tools to enhance data processing, validation, and operational efficiency within the measurement ecosystem.
- Provide essential technical leadership, mentorship, and strategic alignment across multiple organizations within Partner Engineering and Operations, driving best practices and architectural coherence.
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