Data Product Manager
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Key skills for this role
About the Role
Chainalysis is looking for a Data Product Manager to support the Data Products team by owning the design, discovery, and operationalization of data products. The role involves translating business needs into scalable data assets, defining data models, standardizing metrics, and ensuring data quality and adoption.
Key Skills for This Role
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
- Collaborate with Data Engineering to design, build, and optimize scalable, reusable datasets
- 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
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 of business metrics (e.g., ARR, Churn, NRR, LTV:CAC)
- 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
Full Job Posting
Job Title
- Data Product Manager
- Location: Canada (Remote, East Coast)
- The Enterprise Data and Analytics (ED&A) team is responsible for unlocking the value in Chainalysis’ corporate data.
In This Role, You’ll
- 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.
- Collaborate with Data Engineering to design, build, and optimize scalable, reusable datasets.
- Manage the operational lifecycle of data products.
- Drive adoption of standardized datasets by creating clear documentation, examples, and enablement materials.
We’re Looking For Candidates Who Have
- Experience 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 of business metrics (e.g., ARR, Churn, NRR, LTV:CAC).
- 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 Have Experience
- 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.
- 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.
Systems/Tools We Use
- Marketo, Salesforce, NetSuite, Adaptive Insights, Pendo, Fivetran, Dagster, AWS Redshift, Databricks & Databricks Genie, Git/Github Enterprise, SQL, dbt, Python, Tableau, DataGrip, Jira, Confluence
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