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Data Product Manager

Mindlance

San Jose, CA

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JOB DETAILS
SALARY
$69.28–$69.28 Per Hour
SKILLS
Agile Programming Methodologies, Analysis Skills, Atlassian JIRA, Business Intelligence, Cadence, Communication Skills, Continuous Improvement, Cross-Functional, Data Analysis, Data Modeling, Data Processing, Data Quality, Data Science, Data Sets, Data Warehousing, Dimensional Modeling, Documentation, Ecosystems, Establish Priorities, Incident Management, Knowledge Management Systems, Looker, Metrics, Performance Metrics, Power BI, Problem Solving Skills, Product Management, Product Planning, Project/Program Management, Release Management/Engineering, Reporting Dashboards, SQL (Structured Query Language), Scalable System Development, Service Level Agreement (SLA), Sprint Planning, Tableau, Usability Engineering, Use Cases, Wiki
LOCATION
San Jose, CA
POSTED
30+ days ago
- Define and own the long-term vision and roadmap for analytics datasets, governed metrics, and dashboards
- Translate business questions into durable data products (canonical datasets, semantic layers, standardized dashboards)
- Establish and manage a prioritized intake process for analytics requests, balancing quick wins with foundational investments
- Write clear requirements for datasets and dashboards, including metric definitions, grain, dimensions, filters, and refresh expectations
- Partner with Data Engineering to shape data models, pipelines, and data contracts that enable scalable analytics
- Partner with Data Science and Analytics to ensure datasets are analysis-ready and reusable across use cases
- Create and maintain KPI frameworks and single source of truth metric definitions to reduce metric disputes
- Own dashboard strategy: what to build, what to retire, and how to improve usability and adoption
- Implement and run the operating cadence for execution, including Jira epics/stories, sprint planning, prioritization, and release communication
- Maintain a team wiki (e.g., Confluence) with documentation for datasets, dashboards, metric definitions, and usage guidelines
- Drive quarterly planning, resourcing conversations, milestone tracking, and stakeholder reviews of roadmap progress
- Define and track success metrics for data products, including adoption, data quality, freshness, reliability, and stakeholder satisfaction
- Establish monitoring and processes for data quality issues, incident triage, and continuous improvement
- Enable self-serve analytics by improving discoverability, documentation, training, and stakeholder enablement
- Act as the primary cross-functional point of accountability for analytics data products from concept through launch and iteration

- Strong product management skills applied to data and analytics products, including roadmap ownership and prioritization
- Ability to think long-term about foundational data assets, not just short-term reporting outputs
- Excellent stakeholder management and communication skills, with the ability to align teams on shared metric definitions and outcomes
- Proven ability to translate ambiguous business needs into clear requirements for datasets and dashboards
- Working proficiency in SQL and strong fluency in data warehousing concepts, dimensional modeling, and event-based data
- Experience with BI/dashboarding ecosystems (e.g., Looker, Tableau, Power BI) and building scalable dashboard suites
- Familiarity with semantic layers or metric layers and the concept of governed, reusable metric definitions
- Strong execution and program management skills, including sprint rituals, backlog hygiene, and delivery predictability
- Hands-on experience running Jira workflows and building operating mechanisms for intake, planning, and release management
- Ability to create clear documentation and knowledge management systems in a wiki environment (e.g., Confluence)
- Strong intuition for data quality, data reliability, and trust-building through SLAs, validation, and monitoring practices
- Comfort partnering with engineering teams on technical tradeoffs, scope decisions, and delivery planning
- Ability to drive adoption through enablement, training, office hours, and stakeholder feedback loops

EEO:

Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.

About the Company

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Mindlance

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