Data Engineer, YouTube Marketing

About the job

As a Data Engineer for the Global YouTube Marketing team, you will play a vital role in building and maintaining the data infrastructure that fuels our marketing strategy. You will design, develop, and optimize scalable data pipelines, ensuring high data quality and accessibility for analytics and reporting. Your technical expertise will enable the broader marketing organization to leverage data-driven insights to measure and optimize the impact of marketing initiatives.Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

Responsibilities

• Design, develop, and maintain scalable data pipelines and data models to collect, process, and store data from various marketing sources.
• Integrate new metrics into core data marts and establish robust data quality checks and monitoring to ensure data accuracy, integrity, and pipeline stability.
• Collaborate with cross-functional partners to translate business requirements into technical data solutions and infrastructure.
• Optimize data infrastructure and querying layers for performance, efficiency, and scalability to support evolving Global YouTube Marketing needs.

Qualifications

Minimum qualifications:

• 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 managing client-facing projects, troubleshooting technical issues, and working with Engineering and Sales Services teams.
• Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Preferred qualifications:

• Experience in technical consulting.
• Experience working with Big Data, information retrieval, data mining, or machine learning.
• Experience in building multi-tier high availability applications with modern web technologies (e.g., NoSQL, MongoDB, SparkML, TensorFlow).
• Experience architecting, developing software, or internet scale production-grade Big Data solutions in virtualized environments.
• Expertise in designing data models, data warehouses, and handling large-scale distributed data processing.