Senior Product Manager, Data Platform

Curinos • New York, NY

14h • Hybrid

About The Position

Curinos is seeking a Senior Product Manager to lead its Data Platform pod and own the vision, roadmap, and outcomes for the full Curinos Lakehouse on Databricks. The role covers data ingestion, modeling, governance, data products, shared enterprise data assets—including canonical entities and the Customer 360 data layer—and common data platform tooling. It also includes leadership and development of one direct report focused on methodology and semantic governance.

The Data Platform is the shared foundation where Curinos data is ingested, modeled, governed, and made available to products, analytics, and AI. The role will bring datasets together across products, model data centrally, and make it discoverable, governed, and AI-ready within data-use policies. A key priority is expanding the breadth and depth of the Customer 360 data layer. The position partners closely with the Head of Data Strategy on new data asset partnerships, acquisitions, and proofs of concept, including hands-on discovery where useful.

This platform product management role serves product pods, Advisory and analytics teams, and the AI platform. It requires deep Databricks knowledge, an understanding of how a governed data platform enables a Databricks-native AI platform, and the ability to work hands-on with data. The role is open to hybrid or remote candidates based in the United States; Curinos operates under a hybrid modality and has offices in New York, Chicago, Boston, Toronto, and London.

The Senior Product Manager will set the Lakehouse strategy and standards, prioritize investments, and measure platform value through outcomes such as time-to-value, adoption, reuse, reliability, and cost efficiency. The role will make data AI-ready through contracts, metadata, quality checks, semantic layers, and standardized interfaces for models, agents, and MCP-enabled experiences. It will also ensure platform operations, governance, privacy, access controls, and compliance scale appropriately. The salary range is $160,000–$170,000 USD plus bonus.

Requirements

• At least 6 years of Product Management experience, including at least 3 years owning data platform, data infrastructure, or analytics platform products.
• Deep, hands-on understanding of Databricks, including Lakehouse architecture, Unity Catalog, Delta Lake, Databricks SQL, Lakeflow pipelines and jobs, and compute and cost management.
• 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.
• Ability to run a platform as a product for internal customers, drive adoption of shared patterns, balance central standards with pod autonomy, and make prioritization trade-offs.
• Experience with customer-level or entity-level data, including identity resolution, data linkage, and handling sensitive data in a regulated environment.
• 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 ability to work hands-on with data, including writing SQL, exploring and profiling datasets in Databricks notebooks, checking data quality and linkage, and prototyping to validate ideas.
• Ability to consider the broader product suite, AI platform, and future business value of data beyond a single pod.
• Strong communication skills and ability to explain complex data and AI concepts to executives and 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.

Nice To Haves

• 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.

Responsibilities

• Own the Data Platform vision, roadmap, and quarterly outcomes across the full Databricks Lakehouse, including ingestion, modeling, governance, data products, shared enterprise data assets, and the Customer 360 data layer.
• Bring data together across product pods into trusted, well-modeled, discoverable data products across business domains, including Customer 360 gold assets.
• Make data AI-ready through data contracts, complete metadata, in-pipeline quality checks, governed semantic layers, and standardized interfaces for AI models, agents, and MCP-enabled experiences.
• Partner with the AI Platform, App & API Platform, product pods, Data Strategy, Engineering, and Advisory to define reusable patterns and enable teams to adopt them.
• Lead and develop one direct report focused on methodology and semantic governance.
• Partner with the Head of Data Strategy on proofs of concept for new data assets, including hands-on data exploration, linkage testing, Databricks prototyping, and value assessment where appropriate.
• Turn successful data asset proofs of concept into production-ready Lakehouse assets after data-use rights, privacy, and legal reviews are complete.
• Own the Lakehouse as a product, setting standards for how data lands, is modeled, and is promoted to production across bronze, silver, and gold layers.
• Grow the Customer 360 data layer by integrating Curinos datasets into a unified customer-level view in line with client agreements and data-use permissions.
• Define a repeatable intake and operating model for Customer 360 assets, including how they are prioritized and governed.
• Partner with business, legal, compliance, and risk leaders to protect client confidentiality and trust through identity, linkage, privacy, and data-use controls.
• Run discovery with Curinos One product managers, promote shared aggregation and pipeline patterns, and organize data by business domain to support discoverability and reuse.
• Help lead cross-team data architecture reviews for cross-pod data requests and new Customer 360, Curinos One, and Copilot use cases.
• Ensure Databricks operations scale reliably, including compute management, project and workspace setup, permissions, access requests, catalog structure, cost allocation, and compliance controls.
• Partner with Databricks to align enterprise data platform strategy and maturity with industry direction and Databricks platform evolution.
• Define and track platform success measures, communicate progress against quarterly goals, quantify business impact, and use feedback and adoption data to guide investment.
• Balance scalability, reliability, and cost efficiency; make the economics and success measures of platform investments clear to stakeholders.
• Stay current on Databricks capabilities and translate relevant discoveries into a unified Data and AI roadmap.

Benefits

• Competitive financial, health, and lifestyle benefits.
• Flexible working options, including home working and flexible hours; part-time options may be available depending on role requirements.
• Unlimited PTO, floating holidays, volunteering days, and a day off for your birthday.
• Learning and development tools to support career development.
• Regular social events and networking opportunities.
• Collaborative and supportive culture, including an active DE&I program.
• Employee Assistance Program providing third-party advice on wellbeing, relationships, legal and financial matters, and access to counselling services.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed