Lead Data Product Manager

Workiva is a company that provides an AI-powered platform designed for complex organizations. They are seeking a Lead Data Product Manager to own the development of data products that support business operations, working closely with Finance and People & Culture leaders to translate their needs into actionable data solutions.

Responsibilities:

• Partner with Finance and P&C leaders to identify data gaps, prioritize opportunities, and build a roadmap that delivers measurable value
• Design data products that support multiple consumption patterns, including BI tools, AI-enabled experiences, and business applications
• Use data usage patterns — dashboard activity, query volume, and recurring reporting requests — to proactively identify unmet needs
• Translate business objectives into clear requirements, challenging assumptions early to ensure teams are solving the right problems
• Serve as a strategic data partner across business stakeholders, Analytics, and Data Engineering teams
• Facilitate collaboration across functions while identifying shared data needs and reducing siloed solutions
• Build prioritization frameworks that balance competing needs and provide transparency around trade-offs
• Communicate effectively with technical teams, business leaders, and executives
• Own the full product lifecycle across multiple Finance and P&C initiatives, from discovery through Alpha, Beta, and GA releases
• Design user-focused data experiences that balance technical requirements with stakeholder needs
• Define and maintain semantic contracts, including field definitions, metric logic, and data grain specifications
• Identify reusable data assets and scalable models that support multiple downstream use cases
• Maintain a high bar for accuracy, freshness, and reliability while proactively resolving issues before they impact users or AI workflows
• Use AI tooling to improve product workflows, including requirements synthesis, AI-assisted SQL validation, catalog generation, and data pattern analysis
• Define success metrics for each data product and measure adoption and business impact over time
• Develop a deep understanding of end-user workflows and leverage personas to create solutions that address real business needs
• Gather stakeholder feedback after launch and continuously improve products based on usage and outcomes
• Ensure data products are structured and documented to support trusted AI-enabled experiences
• Serve as the product counterpart to Data and Analytics Engineering — owning the what and why while partnering on the how
• Collaborate on semantic layer design and dbt transformations to create consistent metric definitions across BI tools, LLMs, reverse ETL pipelines, and applications
• Identify opportunities to improve ingestion, transformation, and delivery processes while advocating for investments that increase reliability and scalability
• Lead Agile delivery cycles by translating roadmap priorities into Initiatives and Epics with clear acceptance criteria
• Lead data catalog efforts for your product area, including discoverability, lineage tracking, and documentation
• Champion data quality frameworks and governance standards around access controls, retention, and responsible data usage
• Partner across teams to solve systemic data challenges rather than shifting complexity downstream
• Present compelling data stories that help technical and non-technical stakeholders make informed decisions
• Develop enablement resources, including workshops, documentation, and training, to increase adoption of data products
• Build AI literacy across stakeholder communities by helping teams understand how to effectively use AI tools grounded in trusted data
• Contribute reusable components, patterns, and best practices that help the broader Data & Analytics organization accelerate delivery

Requirements:

• 6+ years in product management, with 3+ years focused on data products, analytics platforms, or data infrastructure
• Demonstrated experience building data products in a Finance, HR, Legal, operations, or similar business domain
• Bachelor's degree in Engineering, Computer Science, Data Science, Business, or equivalent experience
• Proven ability to operate in greenfield or early-stage data environments where you've created structure while delivering results
• Strong understanding of data pipelines, dimensional modeling, semantic layers, and modern analytics stacks (dbt, Snowflake, BI platforms)
• Solid understanding of data governance principles, including metadata management, lineage, quality frameworks, and access controls
• Proficiency in SQL with the ability to independently query and validate data
• Exceptional stakeholder management skills across senior business and technical audiences
• Background in SaaS or product-led growth companies
• Experience with data catalog platforms (e.g., Atlan, Alation)
• Familiarity with cloud and data tooling: Cloud: AWS, Snowflake; Transformation & orchestration: dbt, Fivetran, Airflow; Visualization: Quicksight, Omni, Sigma; Analytics: SageMaker, Python (Pandas, Seaborn); Project Management: Jira, Confluence, Figma