Senior Product Manager, Data

Arionkoder

. Lead discovery with business and technical stakeholders through working sessions, surface current data usage, and turn findings into prioritized use cases and requirements .

Posted 10/31/2026full-timeRemoteSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in product management for data products, with a strong focus on stakeholder alignment, evidence-based prioritization, and adoption strategies. Possesses the ability to challenge technical decisions and engage effectively with data architects and engineers.

Highest-signal resume keywords

Product ManagementStakeholder AlignmentData Product DevelopmentAI Product DesignModern Data Stack Familiarity

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data AnalyticsMetrics DefinitionRequirements GatheringHypothesis-Driven ProcessAcceptance Criteria DefinitionTechnical Decision MakingProduct Adoption StrategiesEvidence-Based PrioritizationData ModelingDocumentation

Soft Skills

LeadershipCommunicationDecision MakingCollaborationProblem Solving

Tools & Technologies

DatabricksSnowflakeDbtData CatalogsGovernance Tooling

Industry Keywords

Data ProductsInternal Data ToolsStakeholder EngagementData GovernanceSemantic Layers

Tech Stack

Tools & technologies

Snowflake

About the role

Key responsibilities & impact

Lead discovery with business and technical stakeholders through working sessions, surface current data usage, and turn findings into prioritized use cases and requirements
Own definitions and ownership by identifying inconsistent metrics and business terms and driving agreed, documented definitions with accountable owners
Lead adoption across the business and secure leadership sponsorship and alignment
Run a hypothesis-driven process by validating client assumptions through sessions or experiments and documenting clear verdicts and rationale
Shape increments with the Solution Architect by defining scope, acceptance criteria and vertical-slice order based on value and risk
Challenge technical decisions from a business perspective and push back on unsuitable data models, definitions or trade-offs
Maintain cadence with the Project Manager by tracking decisions, open questions, risks and stakeholder commitments
Transfer ownership through processes, documentation and an ownership model that keeps the layer accurate after engagement

Requirements

What you’ll need

5+ years in product management, with experience on data products (analytics, data platforms, metrics or semantic layers, internal data tools or similar)
Experience aligning stakeholders across business areas on shared definitions, priorities and ways of working
A structured, evidence-based approach to discovery and prioritization
Comfortable making decisions with incomplete information and managing senior stakeholders
A record of getting products adopted, not just delivered
Experience in defining, designing and delivering AI or LLM-based products
Fluent written and spoken English
Enough technical depth to challenge data architects and engineers on technical definitions, modeling choices and trade-offs, and to understand their answers (strong plus)
Familiarity with modern data stacks, for example Databricks, Snowflake, dbt, data catalogs or governance tooling (strong plus)

Benefits

Comp & perks

Monthly USD Service Fee
20 business days of paid Agreed Time Off—Annual + 6 Local Holidays
Caregiver Time Off
A dynamic remote work culture. You can work from anywhere!
An entrepreneurial environment.