Senior Data Engineer, gTech Users and Products

Google LLC; Boulder (CO); On-site; USD 156,000 - 226,000; Full time

Job summary

Google in Boulder is seeking a Senior Data Engineer to drive end-to-end data architectures powering support and product experiences across Google's ecosystem.

You will scope nebulous data challenges, guide technical strategy, and mentor fellow engineers while scaling Google’s data infrastructure. You will design scalable data models, lead telemetry architectures, and integrate AI/ML workflows across large pipelines to deliver actionable insights and robust data solutions.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 5 years 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.).
• 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.

Responsibilities

• Own the architecture, technical roadmap, and priorities for large-scale data products, pipelines, and reporting systems within gUP.
• Scope difficult, nebulous technical problems and deliver robust, optimal solutions without needing continual oversight or steering.
• Lead complex architectural constraints across data sources, target interfaces, storage systems, and latency/frequency requirements while building components that scale cleanly.
• Leverage AI and machine learning techniques to automate workflows and productionize models within large-scale distributed data processing pipelines.
• Partner directly with Users and Products leadership and cross-functional teams to translate strategic business needs into technical data architecture roadmaps.

Skills

Data pipelines

Dimensional data modelling

Programming languages

Data infrastructure

Exploratory queries

Education

Bachelor's degree or equivalent

Master's degree

PhD

Tools

Flume

Dataflow

Spark

Job description

Senior Data Engineer, gTech Users and Products

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info_outline

info_outline X The application window will be open until at least October 12, 2026. This opportunity will remain online based on business needs which may be before or after the specified date. In most instances, this position requires in-person interviews as part of the hiring process.

• 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 (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.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related field.
  
• Experience integrating AI/LLMs or productionizing machine learning models within distributed data pipelines.
  
• Experience mentoring junior data engineers and establishing architectural standards, test coverage, and documentation best practices across teams.
  
• Track record of independently owning and scoping complex, ambiguous technical initiatives from design through production launch.
• Excellent written and verbal communication skills, with demonstrated ability to align and influence cross-functional technical and executive partners.

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.

As a Data Engineer in gUP Engineering, you will drive technical direction and own end-to-end data architectures that power support and product experiences across Google's ecosystem. You will scope nebulous, complex data challenges, guide technical strategy, and mentor fellow engineers while pushing Google’s data infrastructure to scale.
Data Engineers in gUP lead and deliver on designing and scaling workflows to support critical user journeys. They translate complex business and operational problems into robust, highly scalable technical data models and systems visions. In this role, you will lead telemetry and logging instrumentation architectures at scale to generate actionable product and operational insights, as well as integrating AI/ML workflows and modern analytical frameworks into full-stack data solutions. You will also partner with engineering, product, and data science leaders across Google to align technical roadmaps and solve ambiguous problems at scale.

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 diverse 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).

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

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.

As a Data Engineer in gUP Engineering, you will drive technical direction and own end-to-end data architectures that power support and product experiences across Google's ecosystem. You will scope nebulous, complex data challenges, guide technical strategy, and mentor fellow engineers while pushing Google’s data infrastructure to scale.
Data Engineers in gUP lead and deliver on designing and scaling workflows to support critical user journeys. They translate complex business and operational problems into robust, highly scalable technical data models and systems visions. In this role, you will lead telemetry and logging instrumentation architectures at scale to generate actionable product and operational insights, as well as integrating AI/ML workflows and modern analytical frameworks into full-stack data solutions. You will also partner with engineering, product, and data science leaders across Google to align technical roadmaps and solve ambiguous problems at scale.

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 diverse 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).

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $156000 - $226000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google .

• Own the architecture, technical roadmap, and priorities for large-scale data products, pipelines, and reporting systems within gUP.
• Scope difficult, nebulous technical problems and deliver robust, optimal solutions without needing continual oversight or steering.
• Lead complex architectural constraints across data sources, target interfaces, storage systems, and latency/frequency requirements while building components that scale cleanly.
• Leverage AI and machine learning techniques to automate workflows and productionize models within large-scale distributed data processing pipelines.
• Partner directly with Users and Products leadership and cross-functional teams to translate strategic business needs into technical data architecture roadmaps.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.