Lead Data Product Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Define and take ownership of the Data Product Roadmap.

• Collaborate with Finance and People & Culture leaders to pinpoint data gaps, prioritize opportunities, and create a roadmap that delivers measurable value.

• Design data products accommodating various consumption patterns, including BI tools, AI-driven experiences, and business applications.

• Leverage data usage patterns—dashboard activity, query volume, and recurring reporting requests—to proactively identify unmet needs.

• Convert business objectives into precise requirements, challenging assumptions early to ensure teams address the right issues.

• Act as a strategic data partner among business stakeholders, Analytics, and Data Engineering teams.

• Facilitate cross-functional collaboration while identifying shared data needs and minimizing siloed solutions.

• Develop prioritization frameworks that balance competing demands and offer transparency regarding trade-offs.

• Communicate clearly with technical teams, business leaders, and executives.

• Manage the complete product lifecycle across various Finance and People & Culture initiatives, from discovery through Alpha, Beta, and GA releases.

• Design user-centric data experiences that harmonize technical requirements with stakeholder needs.

• Define and uphold semantic contracts, including field definitions, metric logic, and data grain specifications.

• Recognize reusable data assets and scalable models that facilitate multiple downstream use cases.

• Maintain high standards for accuracy, freshness, and reliability while proactively addressing issues before they affect users or AI workflows.

• Utilize AI tools to enhance product workflows, including requirements synthesis, AI-assisted SQL validation, catalog generation, and data pattern analysis.

• Establish success metrics for each data product and track adoption and business impact over time.

• Develop a comprehensive understanding of end-user workflows and leverage personas to create solutions that meet genuine business needs.

• Collect stakeholder feedback post-launch and continuously refine products based on usage and outcomes.

• Ensure data products are structured and documented to support reliable AI-enabled experiences.

• Serve as the product liaison to Data and Analytics Engineering—owning the what and why while collaborating on the how.

• Work together on semantic layer design and dbt transformations to establish consistent metric definitions across BI tools, LLMs, reverse ETL pipelines, and applications.

• Identify opportunities to enhance ingestion, transformation, and delivery processes while advocating for investments that boost reliability and scalability.

• Lead Agile delivery cycles by translating roadmap priorities into Initiatives and Epics with clear acceptance criteria.

• Oversee data catalog initiatives for your product area, including discoverability, lineage tracking, and documentation.

• Advocate for data quality frameworks and governance standards concerning access controls, retention, and responsible data usage.

• Collaborate with teams to address systemic data challenges rather than shifting complexity downstream.

• Present engaging data narratives that enable both technical and non-technical stakeholders to make informed decisions.

• Create enablement resources, including workshops, documentation, and training, to enhance the adoption of data products.

• Foster AI literacy within stakeholder communities by assisting teams in effectively utilizing AI tools grounded in trusted data.

• Contribute reusable components, patterns, and best practices that aid the broader Data & Analytics organization in accelerating delivery.

⛳️ Requirements

• 6+ years of experience in product management, with at least 3 years focused on data products, analytics platforms, or data infrastructure.

• Proven track record of building data products in Finance, HR, Legal, operations, or a related business domain.

• Bachelor’s degree in Engineering, Computer Science, Data Science, Business, or equivalent experience.

• Demonstrated ability to operate in greenfield or early-stage data environments where you’ve established structure while achieving results.

• Strong knowledge of data pipelines, dimensional modeling, semantic layers, and contemporary analytics stacks (dbt, Snowflake, BI platforms).

• Solid grasp 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.

• Experience in SaaS or product-led growth companies.

• Familiarity with data catalog platforms (e.g., Atlan, Alation).

• Knowledge of 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.

🏝️ Benefits

• A discretionary bonus typically awarded annually.

• Restricted Stock Units granted upon hiring.

• 401(k) matching and a comprehensive employee benefits package.