Senior Product Manager, Data Platform

Curinos is seeking a Senior Product Manager to lead the vision, roadmap and outcomes for its Databricks Lakehouse and Data Platform. The role owns shared data assets and tooling, including the Customer 360 data layer, and leads work to make data governed, discoverable and ready for analytics and AI.

Responsibilities:

• Own the Data Platform vision, roadmap and quarterly outcomes across the full Databricks Lakehouse, from ingestion and modeling to governance, data products and shared enterprise data assets, including the Customer 360 data layer
• Bring data from across pods together into trusted, well-modeled data products across business domains, including Customer 360 gold assets, with a central catalog that pods and decisioning use cases can draw from directly
• Make data AI-ready by default through data contracts, complete metadata, in-pipeline data quality checks and governed semantic layers
• Partner with the AI Platform, App & API Platform, product pods, Data Strategy, Engineering and Advisory to define reusable patterns that pods can adopt and build on
• Lead and develop one direct report focused on methodology and semantic governance
• Partner with the Head of Data Strategy on POCs for new data assets, rolling up your sleeves for hands-on discovery where it helps the team move faster
• Ensure Databricks operations are well managed at scale, including compute, permissions, cost allocation and compliance, partnering with the teams that run the platform day to day so operations never slow delivery
• Partner with Databricks to align the enterprise data platform strategy and maturity roadmap with industry direction and Databricks platform evolution

Requirements:

• 6+ years of Product Management experience, including 3+ years of owning data platform, data infrastructure or analytics platform products
• Deep, hands-on understanding of Databricks, including Lakehouse architecture, Unity Catalog, Delta Lake, Databricks SQL, Lake flow pipelines and jobs, and compute and cost management
• Strong working knowledge of how a data platform supports a Databricks-native AI platform, including semantic layers and metric views, Genie, vector search, model serving, agents and MCP-based data access
• Experience with data governance at scale, including catalogs, metadata, lineage, access controls, data contracts and data quality frameworks
• Proven ability to run a platform as a product for internal customers: driving adoption of shared patterns, balancing central standards with pod autonomy and making clear prioritization trade-offs
• Experience with customer-level or entity-level data, including identity resolution, data linkage and handling sensitive data in a regulated environment
• Strong technical fluency to partner with data engineers, architects and data scientists, including comfort with SQL, data modeling and Lakehouse design patterns such as medallion architecture
• Demonstrated experience as a strong individual contributor who is comfortable being hands-on with the data: writing SQL, exploring and profiling datasets in Databricks notebooks, checking data quality and linkage, and prototyping quickly to validate ideas before engaging engineering
• Ability to think beyond a single pod to the broader product suite, the AI platform and the future value data can drive across the business
• Strong communication skills and demonstrated ability to explain complex data and AI concepts to executives and to technical and non-technical stakeholders
• Experience managing, developing, and/or mentoring product managers
• Strong judgment, ownership and follow-through, with the ability to manage multiple workstreams, own quarterly outcomes and make practical trade-offs
• Experience in financial services, fintech, banking or another regulated industry
• Databricks certifications, such as Data Engineer or Generative AI Engineer
• Experience with semantic layers, metrics stores, business catalogs or ontologies
• Experience with third-party data, identity spines, clean rooms or zero-copy data sharing such as Delta Sharing
• Experience with other modern data platforms such as Snowflake