Join our gData team as a Data Engineer and play a crucial role in building and enhancing the core data infrastructure that supports GBO's critical data needs.

You will tackle challenging, large-scale data issues using Google's advanced technology stack to ensure a highly reliable Single Source of Truth. This position offers a unique opportunity to architect innovative data pipelines and solutions that drive predictive problem-solving and AI-powered business decisions at scale.

Google is dedicated to creating products and services that benefit the world. Within gTech, we empower customers globally by providing trusted advisory services. Our expertise stems from technical proficiency, deep product knowledge, and a thorough understanding of our customers' unique challenges. Whether developing custom solutions or scalable new tools, our goal is to maximize the value customers receive from Google products.

Design, develop, test, and maintain robust and scalable data pipelines and ETL/ELT architectures utilizing Google's distributed data systems, including advanced SQL and Python.

Contribute to the ongoing modernization of the Google Ads Data Infrastructure (GDI) and Customer Data Platform (CDP), fine-tuning data models to preserve the integrity and performance of our Single Source of Truth.

Collaborate closely with cross-functional teams across gTech and Customer Engagement (CE) to translate emerging business requirements into effective technical data solutions.

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

Champion data quality by producing clear technical design documentation, conducting code reviews, and proactively addressing complex bugs and support escalations.

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

Possess at least 1 year of experience with data processing tools such as Hadoop, Spark, Pig, and Hive, alongside a strong understanding of algorithms like MapReduce and Flume.

Demonstrate experience in managing client-facing projects, resolving technical challenges, 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.

A Master's degree or other advanced degree in Computer Science or a related technical field, or equivalent practical experience, is preferred.

Experience in technical consulting and working with data warehouses, including their architectures, infrastructure, ETL/ELT processes, and reporting tools, is advantageous.

Familiarity with Big Data environments, information retrieval, data mining, or machine learning concepts is beneficial.

Experience building highly available multi-tier applications using modern web technologies such as NoSQL, MongoDB, SparkML, or TensorFlow is desirable.

Previous experience in a customer-facing or customer service capacity, especially leveraging AI technologies to enhance or automate development processes, is a plus.