Minimum qualifications:

Bachelor's degree in Computer Science, Information Systems, a related technical field, or equivalent practical experience.
3 years of experience in data engineering, database querying (e.g., SQL), developing data pipelines (ETL) and data visualization (dashboards/reports).
3 years of experience coding in one or more programming languages.
3 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
3 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.).

Preferred qualifications:

Master's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience.
3 years of experience partnering with stakeholders (e.g., users, partners, customer), and managing stakeholders/customers.
3 years of experience developing project plans and delivering projects on time within budget and scope.
Experience using AI technologies to augment, improve or automate the development process.
Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources.
Experience in large-scale distributed data processing, including familiarity with NoSQL databases.

About the job:

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 investigative issues. Ultimately, our insights optimize operations and enhance the advertiser experience that drives the majority of Alphabet's business.

As a Data Engineer in gData, you will design and build the foundational data infrastructure that powers the global gTech Ads organization. You’ll address complex, large-scale issues using Google’s proprietary tech stack to deliver a reliable single source of truth. In this role, 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.

To learn more about gTech, check out our video.

Responsibilities:

Design, develop, test, and maintain reliable and scalable data pipelines and Extract, Transform, and Load (ETL)/Extract, Load, and Transform (ELT) architectures using Google's distributed data systems (e.g., advanced SQL, Python).
Contribute to the development of our data infrastructure and data platform, optimizing data models to ensure our single source of truth remains performant.
Partner closely with cross-functional stakeholders across business and engineering teams to translate evolving analytics requirements into actionable technical data solutions.
Work seamlessly with data scientists and business analysts to transition investigative prototypes, metrics, and models into stable, production-grade reporting environments.
Advocate data quality by authoring clear technical design documents, executing code reviews, and proactively resolving complex bugs and supporting escalations.

Data Engineer, Data Architecture and Engineering

Job Description