Data Engineer, Data Architecture and Engineering, gData

Google•Boulder, CO

19h•$130,000 - $188,000

About The Position

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. The gSO Data, Architecture, Tools and Analytics (gData) team empowers Google to make brilliant business decisions by delivering critical data infrastructure and actionable insights. Supporting the global gTech Ads organization, gData manages massive datasets to solve complex, non-routine analytical challenges. Ultimately, our insights optimize operations and enhance the advertiser experience that drives the majority of Alphabet's business generation. Within gData, the Data Architecture and Engineering (DArE) team are the proud owners of the gTech Ads Single Source of Truth for operations data. We partner cross-functionally across strategy, analytics, and engineering to build reporting infrastructure that is stable, scalable, and highly trusted. DArE ensures that users at all levels have access to the accurate, aligned metrics needed to power a thriving Ads ecosystem. As a Data Engineer in gData, you’ll design and build the foundational data infrastructure that powers the GBO data needs. You’ll manage complex, large-scale challenges using Google’s proprietary tech stack to deliver a highly reliable single source of truth. You will have the opportunity to architect innovative data pipelines and solutions that directly enable predictive analytics and AI-driven business decisions at scale. 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.

Requirements

Bachelor's degree in Computer Science, Mathematics, a related field, or equivalent practical experience.
3 years of experience with data processing software (e.g., Hadoop, Spark, Pig, Hive) and algorithms (e.g., MapReduce, Flume).
Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
Experience managing client-facing projects, troubleshooting technical issues, and working with engineering and sales services teams.

Nice To Haves

Master's degree or other advanced degree in Computer Science, or a related technical field, or equivalent practical experience.
Experience managing projects and working with analytics, software coding, or customer-side web technologies.
Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources, and designing data warehouses, especially for business performance management.
Experience in large-scale distributed data processing, including familiarity with NoSQL databases, with excellent communication, organizational, and analytical skills.
Proficiency in all aspects of the software development cycle, and with using AI technologies to augment, improve or automate the development process.

Responsibilities

Design, develop, test, and maintain reliable and scalable data pipelines and ETL/ELT architectures using Google's distributed data systems (e.g., advanced SQL, Python).
Contribute to the modernization of the Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), optimizing data models to ensure our single source of truth remains robust and performant.
Partner closely with cross-functional stakeholders across gTech and Customer Engagement (CE) to translate evolving business requirements into actionable technical data solutions.
Work seamlessly with Data Scientists and Business Analysts to transition analytical prototypes, metrics, and models into stable, production-grade reporting environments.
Lead data quality by authoring clear technical design documents, executing rigorous code reviews, and proactively resolving complex bugs and supporting escalations.