Data Engineering Manager: AI-Driven Platform Lead

Google LLC; Mountain View (CA); Presencial; USD 186.000 - 269.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Bonus

Benefits

Descripción de la vacante

Google Mountain View, CA, USA is seeking a Manager, Data Engineering to lead the Data and Analytics Services team and guide scalable data infrastructure design. You will partner with stakeholders to translate business needs into robust data solutions and set high standards for data quality and governance.

This role requires strong technical leadership, hands-on experience with large datasets, and the ability to drive architecture decisions across teams. In-person interviews are expected.

Formación

• Bachelor's degree or equivalent practical experience.
• 10 years of data infrastructure and data model experience via queries and scripts.
• 5 years of coding in one or more languages, building data pipelines and scalable architectures.
• 3 years in a people management, supervision, or leadership role.

Responsabilidades

• Define the technical strategy for the centralized data warehouse, scalable pipelines, ETL/ELT processes and AI-ready data foundations.
• Oversee data modeling and SQL transformation standards, guiding architecture and optimization for analytics at scale.
• Drive data quality, governance, and reliability across the organization.
• Partner with executives, data scientists, and engineering to translate needs into prioritized roadmaps.
• Manage resources to deliver projects on time while promoting best practices like reviews.

Conocimientos

Data engineering leadership

Data infrastructure design

SQL / scripting

People management

BigQuery / GCP

Educación

Bachelor's degree or equivalent practical experience

Herramientas

BigQuery

ETL/ELT tools

Python/Java/Scala

Descripción del empleo

Google Mountain View, CA, USA is seeking a Manager, Data Engineering to lead the Data and Analytics Services team and guide scalable data infrastructure design. You will partner with stakeholders to translate business needs into robust data solutions and set high standards for data quality and governance.

This role requires strong technical leadership, hands-on experience with large datasets, and the ability to drive architecture decisions across teams. In-person interviews are expected.