Join our gData team as a Data Engineer and play a crucial role in constructing the core data infrastructure that supports GBO's data requirements. You will tackle intricate, large-scale challenges utilizing Google's proprietary technology to ensure a highly dependable Single Source of Truth. This position offers the chance to architect cutting-edge data pipelines and solutions, directly enabling predictive problem-solving and AI-driven business decisions at scale. Google is dedicated to creating products and services that enhance the world, and gTech is instrumental in bringing these innovations to fruition. Our global teams of trusted advisors leverage deep technical expertise, product knowledge, and a comprehensive understanding of customer needs to deliver exceptional support. Whether crafting bespoke solutions for unique issues or developing scalable tools for Google-wide application, our objective is to empower customers to fully leverage Google products.

Architect, develop, and maintain robust, scalable data pipelines and ETL/ELT frameworks using Google's distributed data systems, including advanced SQL and Python.

Contribute to the ongoing enhancement of the Google Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), optimizing data models to uphold the integrity and performance of our Single Source of Truth.

Collaborate effectively with cross-functional gTech and Customer Engagement (CE) teams to translate dynamic business requirements into practical, technical data solutions.

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

Champion data integrity through the creation of clear technical design documentation, diligent code reviews, and proactive resolution of complex bugs and support escalations.

A Bachelor's degree in Computer Science, Mathematics, or a related discipline, or equivalent practical experience.

One year of experience with data processing tools such as Hadoop, Spark, Pig, or Hive, and familiarity with algorithms like MapReduce and Flume.

Proven experience in managing client-facing projects, adept at troubleshooting technical issues, and collaborating with Engineering and Sales Services teams.

Proficiency in database administration techniques or data engineering, coupled with software development skills in languages like Java, C++, Python, Go, or JavaScript.

Master's degree or an advanced degree in Computer Science or a comparable technical field is preferred, along with experience in technical consulting and working with data warehouses. This includes understanding data warehouse architectures, infrastructure, ETL/ELT processes, and reporting/analytic tools. Experience with Big Data, information retrieval, data mining, machine learning, building high-availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow), and customer-facing roles using AI technologies is also highly valued.