Data Product Manager

Chainalysis • Toronto, ON

18d • Remote

About The Position

The Enterprise Data and Analytics (ED&A) team is responsible for unlocking the value in Chainalysis’ corporate data. We work with internal stakeholders in GTM, Operations and Finance. Our goal is to accelerate Chainalysis’ growth and empower our employees to do their best work. We are looking for a Data Product Manager to support the Data Products team by owning the design, discovery, and operationalization of data products. This role will be responsible for translating business needs into scalable, well-defined data assets and ensuring their ongoing quality, usability, and adoption. The ideal candidate will partner closely with Data Engineering, Data Operations, and business stakeholders to define data models, standardize metrics, and maintain high-quality documentation, ensuring enterprise data products are reliable, consistent, and usable. They will bring experience at the intersection of data, analytics, and product thinking, and are comfortable translating ambiguous stakeholder needs into structured, scalable data solutions while maintaining strong operational rigor.

Requirements

• Experience working as Data Product Manager, Data Strategist, or in a product-oriented, data-focused environment
• Strong understanding of data ecosystems, including data warehousing, modeling, and analytics workflows
• Experience working with cross-functional teams including Data Engineering and business stakeholders
• Experience translating complex business problems into clear product requirements and scalable data solutions
• Strong understanding business metrics (eg: ARR, Churn, NRR, LTV:CAC) and how they are used in decision making
• Experience creating and maintaining documentation in tools like Confluence
• Excellent stakeholder management and communication skills
• Strong analytical and problem-solving skills with a data-driven mindset
• Experience driving product adoption and measuring impact

Nice To Haves

• Experience in enterprise SaaS environments with knowledge of Go-To-Market and Quote-to-Cash processes
• Familiarity with tools such as Databricks, Snowflake, dbt, Tableau or Looker
• Experience working with AI-powered analytics tools (e.g., Databricks Genie or similar)
• Exposure to data governance, or data catalog tools
• Technical background in SQL or analytics engineering
• Familiarity with Salesforce, NetSuite, or other GTM/Finance systems
• Experience working in Agile environments using tools like Jira

Responsibilities

• Partner with stakeholders to translate business problems into clear data product use cases and scalable data solutions
• Define and standardize metric definitions and semantic layers by establishing clear business logic, calculation rules, and hierarchies to ensure consistency, accuracy, and alignment across reporting
• Collaborate with Data Engineering to design, build, and optimize scalable, reusable datasets that consolidate, refresh, and make data easily accessible to stakeholders
• Manage the operational lifecycle of data products, including updates, issue resolution, and performance tracking
• Drive adoption of standardized datasets by creating clear documentation, examples, and enablement materials

What This Job Offers

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