Product Manager, Data Processing
Product Manager, Data Processing
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in product management or a related technical role.
Preferred qualifications:
- 3 years of experience in product management, database systems, ETL, data lakes/warehouses, or Online Analytical Processing.
- Experience in life-cycle data rollouts , promoting product excellence and collaboration.
- Experience in leading cross-organizational efforts interacting with multiple director-level stakeholders.
- Experience working as a software engineer or in a similar technical role.
- Ability to deliver initiatives enabling teams to deliver products while creating solutions to generate data insights.
About the job
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
Responsibilities
- Partner with senior-level engineering leadership in multiple product areas to identify needs and practices in order to build and bring to data processing products that deliver impact for Google.
- Build direction and strategy, and drive execution for Data Processing products. Understand processing models like batch Extract, Transform, Load (ETL), and streaming, how they interface with data lakes/warehouses, and analytics in various contexts (product analysis, experiment analysis etc.).
- Work with cross-product teams to build integrated solutions based on Core Data’s product portfolio, simplifying data management and governance for our customers.
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