Senior Data Product Manager

Were looking for a senior Data Product Manager to drive the strategy, architecture, and execution of the data products that power us. This role is at the core of our data innovation engine, serving multiple business units and platform products across the company. You will lead cross-functional efforts to define, deliver, and scale data assets that are foundational to the product and its market differentiation.
This role offers a unique opportunity to lead high-scale, high-impact data products by collaborating with R&D, product, and business stakeholders to architect modular, trusted, and intelligent data systems.
We're looking for a true data enthusiast: someone passionate about translating business needs into data solutions, building strong relationships, shaping methodologies and processes, and owning complex data initiatives from end to end.
This role will report to the VP of Product Management, Data.
What Youll Do:
Data Product Ownership
Own the vision, roadmap, and delivery of critical datasets that underpin platform functionality, decisioning systems, and customer-facing features.
Lead modularization of data structures to enable scalability, easier ownership distribution, and data quality improvements.
Introduce metrics for quality (completeness, coverage, freshness, accuracy) and define validation, logging, and governance frameworks.
Cross-Functional Leadership
Serve as the product voice for data across R&D, aligning platform engineers, analysts, scientists, and business teams around a common strategy.
Bridge between domain-specific product teams and platform data infrastructure, translating business needs into scalable, reusable data assets.
Define data SLAs, fallback mechanisms, enrichment strategies, and quality assurance mechanisms in partnership with data consumers.
Strategic Impact
Prioritize and plan data initiatives that support new verticals, geographies, product features, and business models.
Spearhead productization of internal datasets into revenue-generating assets for both direct sales and platform distribution.
Deeply understand the customers evolving needs and enable the data to capture them accurately and scalably.
Execution & Optimization
Write clear product specs that include technical definitions, mapping rules, edge case handling, and downstream consumption logic.
Work hands-on with Databricks, Spark, SQL, and Python to analyze datasets, test logic, or collaborate on experiments.
Identify data anomalies, misclassifications, and inconsistencies, and lead efforts to resolve them in systematic and productized ways.
Design workflows for historical tracking and versioning of datasets.