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.
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).
The US base salary range for this full-time position is $106,000-$151,000 + 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
- Design, develop, and support data pipelines, warehouses, and reporting systems, leveraging AI to integrate data into full-stack software solutions.
- Create robust ETL pipelines and reporting systems for new data while continuously improving existing data models and workflows.
- Partner with stakeholders and support engineers to ensure data infrastructure evolves with business, product, and user requirements.
- Work closely with data scientists to scale and transition statistical and machine learning models into production pipelines.
- Write and review clear technical documentation while driving innovation through new analytical tools to unlock deeper data insights.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 1 year of experience coding in one or more programming languages.
- 1 year 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 (DataFlow, Spark, etc.).
- Experience working with data models by performing exploratory queries and scripts.
Preferred qualifications:
- 1 year of experience partnering with stakeholders to deliver projects on time, within budget, and scope.
- Experience writing and maintaining ETLs for structured and unstructured data sources.
- Experience modeling complex business processes or real-world data sources.
- Experience in designing data models, data warehouses, and managing distributed data processing.
- Familiarity with non-relational (NoSQL) data storage systems and Unix/Linux environments.
- Excellent written communication and organizational skills.