Data Engineer, Data Architecture and Engineering, gData

About the role

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.

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.

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.

Preferred qualifications

• 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.

Benefits

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $130000 - $188000 (USD) + 15% bonus target + equity + benefits

Pay

$130000 - $188000 (USD)

Schedule

TBD