Senior Manager, Data Product Manager

The Senior Manager, Data Product Manager role responsible for defining product strategy, direction, and outcomes for cross-domain initiatives within the Finance Data Platform. This role owns the product development lifecycle for platform-level data products from concept and prioritization through delivery and adoption while working in close partnership with Domain Data Product leaders, Data Architecture & Modeling, Data Governance, Engineering, and Program/Project Management.

This role establishes the engagement model for how Finance partners with the Finance Data Platform and ensures product clarity, technical alignment, and AI-readiness across all initiatives.

Product Strategy & Product Development Lifecycle:

• Own and drive the end-to-end Product Development Lifecycle (PDLC) for Finance Data Platform initiatives: discovery, definition, build, validation, and adoption.
• Define product vision, value propositions, success metrics, and phased roadmaps for cross-domain data products.
• Clearly articulate product scope, user stories, and acceptance criteria that reflect Finance business outcomes and technical standards.
• Drive product strategy aligned to Finance priorities, platform maturity, and AI enablement goals.
• Define and operationalize the engagement model for how Finance teams interact with the Finance Data Platform (intake, prioritization, delivery, and adoption).
• Serve as the primary point of coordination for cross-domain Finance initiatives that span Revenue, Expense, Deals, FP&A, Controllership, Tax, and Treasury.
• Ensure Finance stakeholders understand what the platform delivers, how to engage, and what standards apply.

Partnership with Program / Project Management:

• Partner closely with Program and Project Managers by providing clear product priorities and sequencing, well-defined scope and acceptance criteria, dependency context and decision clarity, and participation in planning and alignment forums to ensure shared understanding of product intent.
• Support program updates with product context and outcome-based narratives.

Director-Level & Cross-Domain Coordination:

• Work across Domain Data Product Directors to align shared initiatives and resolve cross-domain dependencies.
• Partner with the Director – Finance Data Architecture & Modeling to ensure semantic consistency, canonical models, and interoperability.
• Collaborate with the Director – Finance Data Governance to ensure all products meet governance, quality, and certification standards.

Technical Product Leadership:

• Engage deeply in technical design discussions and validate feasibility of product requirements.
• Spark SQL
• Hadoop ecosystems (Hive, HDFS, Spark)
• Databricks (Delta Lake, Unity Catalog)
• Snowflake (performance optimization, data sharing)
• Ensure products are designed for scale, performance, auditability, and downstream analytics (Tableau, Power BI).

AI Enablement & Advanced Analytics:

• Drive AI-readiness of Finance data products through strong feature definition and data quality standards.
• Leverage prior experience enabling AI/ML in products using tools such as:
• Databricks MLflow
• Databricks Feature Store
• AWS Sage Maker
• Snowflake Cortex
• Vector databases (e.g., Pinecone, FAISS)
• Partner with Architecture and Governance leaders to ensure explainability, lineage, and responsible AI usage.
• Translate AI capabilities into tangible Finance use cases (forecasting, anomaly detection, insights automation).

Executive Communication & Product Storytelling:

• Develop and deliver executive-ready presentations articulating tradeoffs and sequencing, progress and outcomes.
• Influence senior Finance and Technology leaders through clear, structured storytelling.
• Represent the Finance Data Platform in leadership forums with confidence and clarity.

This is a hybrid position. Expectation of days in office will be confirmed by your hiring manager.

• 8-12+ years in Data Product Management, Data Platform, or Finance Analytics roles.
• Proven success operating as an individual driving cross-functional initiatives.
• Demonstrated ownership of product development life cycles for data or platform products.

• Strong hands-on expertise with Spark SQL.
• Experience with Hadoop,…