US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Develop data policies and educate cross-functional partners to ensure the accuracy and accessibility of Google's global network infrastructure data.
Scale network data systems and processes in collaboration with partner teams to optimize business efficiency.
Oversee tactical data projects, ETL workflow development, and contractor-led data entry operations.
Partner with cross-functional leadership to synchronize project schedules and organizational priorities.
Guide the integration of AI/ML frameworks to automate physical inventory data auditing, proactively identifying anomalies to accelerate data reconciliation and guarantee high integrity.
Minimum qualifications
Bachelor's degree in a technical field or equivalent practical experience.
5 years of experience in program management.
Experience with big data concepts or technologies (e.g., analytics warehousing, data transformation, data governance, data migrations, or performance or scalability optimizations, etc.).
Experience working with data analytics tools (e.g., SQL, BigQuery, R, etc.) and reporting platforms (e.g., Tableau, Microstrategy, Business Objects, etc.).
Preferred qualifications
5 years of experience managing cross-functional or cross-team projects.
Experience in data analytics, warehousing, extract, transform, load (ETL) development, data science, or other big data applications.
Experience with relational database design and development (e.g., SQL, MSSQL, Oracle, PostgreSQL, or MySQL).
Experience with administration of high-availability cloud-based ESRI ArcGIS enterprise software instances with internal workflows, processes, and pipelines.
Knowledge in data networking architectures and physical network components.
Bachelor's degree in a technical field or equivalent practical experience.
5 years of experience in program management.
Experience with big data concepts or technologies (e.g., analytics warehousing, data transformation, data governance, data migrations, or performance or scalability optimizations, etc.).
Experience working with data analytics tools (e.g., SQL, BigQuery, R, etc.) and reporting platforms (e.g., Tableau, Microstrategy, Business Objects, etc.).
