Senior Data Infrastructure Manager, YouTube Marketing
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Please submit your resume in English - we can only consider applications submitted in this language.
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 or equivalent practical experience.
- 10 years of experience working with data infrastructure and data models by performing exploratory queries and scripts.
- 5 years of experience coding in one or more programming languages, and designing data pipelines, and dimensional data modeling for synchronous and asynchronous system integration and implementation using internal and external stacks.
- 3 years of experience in a people management, supervision, or team leadership role.
- Experience in SQL, building dashboards, data collection/transformation, visualization/dashboards, or a scripting/programming language (e.g., Python).
Preferred qualifications:
- Experience working with advanced analytics solutions involving machine learning and statistical analytics.
- Experience supporting client-side media and marketing data science.
- Understanding of incrementality measurement methodologies and frameworks.
- Ability to operate in a fluid, constantly evolving and collaborative environment.
YouTube’s reach and engagement is exceptional. YouTube has become the expressive platform of a generation empowered to shape what matters in culture and society today. Together we are building a global destination for creativity, learning, and expression.
YouTube/Video Global Solutions is the link between Google video products and sales. Our mission is to fuel innovation that keeps YouTube and Video free and accessible to the world. We do this by translating global market needs into meaningful product solutions that drive business results for content partners and customers.
- Build, mentor, and inspire a team of data engineers in delivering scalable and reliable data solutions, fostering a culture of collaboration, innovation, and professional growth.
- Develop, architect and optimize robust data pipelines, ensuring data quality, accuracy, and scalability to meet the evolving needs of the business.
- Partner with cross-functional teams (marketing, data science, engineering, analytics) to build data models, automate processes, and unlock actionable insights that drive business decisions and results.
- Collaborate with key stakeholders to shape the overall data strategy, advocating centralized data infrastructure that empowers reporting, analytics, and data science initiatives across the organization.
- Mentor the team on data engineering best practices, ensuring adherence to industry standards and driving the development of solutions to address complex business challenges.