Join our gTech Strategy and Operations team as a Data Engineer, contributing to the core data infrastructure that supports GBO's critical needs. You will architect and build robust data pipelines utilizing Google's advanced technology stack to ensure a reliable Single Source of Truth. This role offers a unique opportunity to develop innovative data solutions that drive predictive problem-solving and AI-powered business decisions at scale.

Google is dedicated to creating products that positively impact the world, and gTech plays a vital role in bringing these innovations to fruition. Our global teams provide expert support to customers, leveraging deep technical expertise, product knowledge, and an understanding of complex client requirements. Whether developing custom solutions or scalable tools, our focus is on maximizing customer benefits from Google's full product potential. Explore gTech further in our video.

Design, develop, and maintain scalable and reliable data pipelines, including ETL/ELT architectures, using Google's distributed data systems with advanced SQL and Python.

Contribute to the ongoing modernization of the Google Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), optimizing data models for peak performance and data integrity.

Collaborate effectively with cross-functional teams within gTech and Customer Engagement (CE) to translate business needs into robust technical data solutions.

Work closely with Data Scientists and Business Analysts to transition analytical prototypes, metrics, and models into production-ready reporting environments.

Champion data quality through clear technical documentation, rigorous code reviews, and proactive resolution of complex issues and escalations.

A Bachelor's degree in Computer Science, Mathematics, or a related technical field, or equivalent practical experience, is required. Candidates should possess at least 1 year of experience with data processing software like Hadoop and Spark, and algorithms such as MapReduce.

Experience in managing client-facing projects, resolving technical challenges, and collaborating with Engineering and Sales Services teams is essential. Proficiency in database administration, data engineering, and software development using languages like Java, C++, Python, Go, or JavaScript is also necessary.

Preferred qualifications include a Master's degree or higher in Computer Science or a related technical discipline. Experience in technical consulting, data warehousing, and working with Big Data, information retrieval, data mining, or machine learning concepts is highly advantageous. Familiarity with building high-availability applications using modern web technologies and AI-driven development automation is a plus.