Data Engineer, YouTube Marketing
Indexed description
Only applications of candidates with Mexican citizenship will be evaluated for this role in compliance with the provisions of Article 7 of the Federal Labor Law.
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.
- 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.
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.
Create a free Caio profile to unlock more results and save your role and location preferences.
Unlock free search