Chainalysis
Technology
DataProductManager
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Product Manager at Chainalysis. Skills: Data Product Management, Data Strategy, Analytics, Product Thinking. Own design of data products. Own discovery of data products”
Industry & Context.
Analytical; Problem-solving; Data-driven mindset
What They're Looking For.
Must Have
Experience as Data Product Manager, Experience as Data Strategist, Experience in product-oriented, data-focused environment, Understanding of data ecosystems, Understanding of data warehousing, Understanding of data modeling, Understanding of analytics workflows, Experience with cross-functional teams, Experience with Data Engineering, Experience with business stakeholders, Experience translating business problems, Experience creating documentation, Experience maintaining documentation, Analytical skills, Problem-solving skills, Experience driving product adoption, Experience measuring impact
Nice to Have
Experience in enterprise SaaS environments, Knowledge of Go-To-Market processes, Knowledge of Quote-to-Cash processes, Familiarity with Databricks, Familiarity with Snowflake, Familiarity with dbt, Familiarity with Tableau, Familiarity with Looker, Experience with AI-powered analytics tools, Exposure to data governance, Exposure to data catalog tools, Technical background in SQL, Technical background in analytics engineering, Familiarity with Salesforce, Familiarity with NetSuite, Familiarity with GTM systems, Familiarity with Finance systems, Experience in Agile environments
What You'll Do.
Own design of data products
Own discovery of data products
Own operationalization of data products
Translate business needs into data assets
Ensure data product quality
Ensure data product usability
Ensure data product adoption
Partner with Data Engineering
Partner with Data Operations
Partner with business stakeholders
Maintain documentation
Translate business problems into use cases
Translate business problems into data solutions
Define metric definitions
Standardize semantic layers
Establish business logic
Establish calculation rules
Establish hierarchies
Design scalable datasets
Build scalable datasets
Optimize scalable datasets
Manage operational lifecycle
Manage issue resolution
Manage performance tracking
Drive adoption of datasets
Create enablement materials
How You'll Work.
Team & Collaboration
Cross-functional teams; Data Engineering; Data Operations; Business stakeholders
Communication Scope
Stakeholder communication
Process & Methodology
Agile environments
Full Job Description
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. 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. 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 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 We’re looking for candidates who have: - Experience working as Data Product Manager, Data Strategist
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