Senior Data Engineer, gTech Users and Products

Minimum qualifications:

• Bachelor’s degree in Engineering, Computer Science, Data Science, Statistics, a related field, or equivalent practical experience.
• 5 years of experience coding with one or more programming languages (e.g., Python, Java, JavaScript).
• 5 years of experience analyzing data, database querying (e.g., SQL), and creating dashboards/reports.
• 5 years of experience designing data pipelines (ETL) and dimensional data modeling for synch and asynch system integration and implementation.

Preferred qualifications:

• Master’s degree in Engineering, Computer Science, Business, or a quantitative field.
• 5 years of experience partnering with stakeholders (e.g., users, partners, customers), troubleshooting technical issues, and delivering projects on time within budget and scope.
• 5 years of experience applying quantitative/statistical models to real-world business problems, including effective experimental design, training, data analysis, survey design, and statistical modeling.
• Experience working with Machine Learning and Generative AI.
• Excellent communication skills, with the ability to adapt your message to both technical and business audiences.

About the job:

In gTech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration, and more).

Within gUP, the Machine Learning (ML) Data Services team provides scalable data services that support numerous AI initiatives across Google, enhancing user experience and engagement. We seek entrepreneurial and detail-oriented individuals driven to bring Google AI/ML products to market and to our partners.

This multifaceted role combines deep data analysis with partner consultation. You will act as a technical expert, providing scalable solutions and troubleshooting for partners while advocating for product improvements. A key focus will be conducting end-to-end analysis of large, complex datasets using advanced statistical methods to solve challenging problems and pioneering new methodologies to measure the performance and quality of complex Generative AI models.

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.

To learn more about gTech, check out our video.

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:

• Provide consultation to partners facing daily challenges, delivering innovative and scalable solutions, and performing technical troubleshooting to address their problems and pain points.
• Advocate for new product features and ensure timely and accurate resolution of technical issues.
• Analyze large and complex datasets to solve challenging, non-routine problems using advanced problem-solving techniques. Execute end-to-end analyses encompassing data acquisition, requirement definition, exploratory analysis, model creation, and the presentation of findings to business stakeholders and executives through both written reports and verbal presentations.
• Apply statistical methods to analyze large-scale datasets, solve complex problems, and present actionable recommendations to stakeholders.
• Explore, create, and assess methodologies for measuring complex Generative AI models.