Senior Product Manager, Data

CoreWeave•Sunnyvale, CA

1d•$143,000 - $210,000•Hybrid

About The Position

As a Data Product Manager for Data Infrastructure and Analytics, you will help drive data ingestion, transformation, governance, and analytics enablement. You will collaborate with engineering, analytics, finance, and business teams to help deliver data lake and pipeline orchestration solutions, ensuring accessible data for business insights. Own and evangelize Data Platform and Business Analytics roadmap and strategy across CoreWeave Assist with the execution of CoreWeave’s enterprise data architecture, helping enable the data lake and domain-driven data layer. Support the development and enhancement of data ingestion, transformation, and orchestration pipelines for scalability, efficiency, and reliability. Work with the Engineering and Data teams to maintain and enhance data pipelines for both structured and unstructured data, enabling efficient data movement across the organization. Collaborate with Finance, GTM, Infrastructure, Data Center, and Supply Chain teams to help unify and model data from core systems (ERP, CRM, Asset Mgmt, Supply Chain systems, etc.). Contribute to data governance and quality initiatives, focusing on data consistency, lineage tracking, and compliance with security standards. Support the BI and analytics layer by partnering with stakeholders to enable data products, dashboards, and reporting capabilities. Help prioritize data-driven initiatives, ensuring alignment with business goals and operational needs in coordination with leadership. Remain informed of emerging data technologies and recommend tools and frameworks for improved data management as appropriate.

Requirements

5+ years of experience in data product management, data architecture, or enterprise data engineering roles.
Familiarity with data lakes, data warehouses, ETL/ELT and streaming pipelines, and data governance frameworks.
Hands-on experience with modern data stack technologies (such as Snowflake, BigQuery, Databricks, Apache Spark, Airflow, DBT, Kafka).
Understanding of data modeling, domain-driven design, and creating scalable data platforms.
Experience supporting the end-to-end data product lifecycle, including requirements gathering and implementation.
Strong collaboration skills with engineering, analytics, and business teams to help deliver data initiatives.
Awareness of data security, compliance, and governance best practices.
Understanding of BI and analytics platforms (such as Tableau, Looker, Power BI) and supporting self-service analytics.

Nice To Haves

You’re curious about AI developer tooling and infrastructure.
You have strong problem-solving skills with a proactive and analytical mindset.
You have excellent communication skills and a demonstrated ability to work collaboratively in a fast-paced environment.

Responsibilities

Drive data ingestion, transformation, governance, and analytics enablement.
Collaborate with engineering, analytics, finance, and business teams to help deliver data lake and pipeline orchestration solutions, ensuring accessible data for business insights.
Own and evangelize Data Platform and Business Analytics roadmap and strategy across CoreWeave
Assist with the execution of CoreWeave’s enterprise data architecture, helping enable the data lake and domain-driven data layer.
Support the development and enhancement of data ingestion, transformation, and orchestration pipelines for scalability, efficiency, and reliability.
Work with the Engineering and Data teams to maintain and enhance data pipelines for both structured and unstructured data, enabling efficient data movement across the organization.
Collaborate with Finance, GTM, Infrastructure, Data Center, and Supply Chain teams to help unify and model data from core systems (ERP, CRM, Asset Mgmt, Supply Chain systems, etc.).
Contribute to data governance and quality initiatives, focusing on data consistency, lineage tracking, and compliance with security standards.
Support the BI and analytics layer by partnering with stakeholders to enable data products, dashboards, and reporting capabilities.
Help prioritize data-driven initiatives, ensuring alignment with business goals and operational needs in coordination with leadership.
Remain informed of emerging data technologies and recommend tools and frameworks for improved data management as appropriate.