Data Product Manager

IntoneCCM; Minnesota; On-site; USD 112,000 - 156,000; Full time

Job summary

Intone Inc is seeking a Data Product Manager for a six-month contract based in St Paul, Minnesota. You will lead the strategy, roadmap, and execution of data product initiatives aimed at transforming legacy systems into scalable, high-value assets.

You will partner with data engineering, data science, analytics, and business teams to mature data practices and enable better decision-making. This role requires hands-on leadership across end-to-end product lifecycle, strong governance, and

Qualifications

• Experience leading data product initiatives across data platforms, analytics tools, and ML infrastructure.
• Ability to translate business needs into data-driven product requirements and roadmaps.
• Proven success delivering measurable outcomes through data capabilities and governance.
• Strong communication and stakeholder management to align across teams.

Responsibilities

• Define vision and roadmap for data products, including platforms and analytics tools.
• Partner with data engineers/scientists to build scalable pipelines and services.
• Lead end-to-end lifecycle: requirements, design, development, testing, launch, iterations.
• Translate business logic into data transformations, metadata, and rules.
• Design dashboards, KPIs, and reporting frameworks with analytics teams.
• Define success metrics and monitor product adoption and impact.
• Uphold data governance, privacy, and ethical AI standards.

Skills

Data management

Data analytics

Data engineering

Product leadership

SQL

Data lakes

ETL

Stakeholder management

Communication

Tools

dbt

Looker

Tableau

Power BI

Google Analytics

Databricks

Python

Java

Job description

We are hiring a Data Product Manager for a 6-month contract position based in St Paul, Minnesota. In this role, you will lead the strategy, roadmap, and execution of significant data product initiatives designed to transform legacy systems into scalable, high-value assets. You will partner across data engineering, data science, analytics, and business teams to mature data practices, migrate to modern data platforms, and enable better decision-making and operational efficiency across the enterprise.

Responsibilities

• Define vision and roadmap for data products, including data platforms, analytics tools, and ML infrastructure.
• Identify high-value opportunities by investigating the data landscape, pain points, and business needs.
• Align data product strategy with organizational priorities and long-term data architecture in partnership with Enterprise Architecture and stakeholders.
• Connect data capabilities to business outcomes and organize efforts to achieve measurable results.
• Lead the end-to-end lifecycle of data products: requirements, design, development, testing, launch, and iteration.
• Partner with data engineers and data scientists to build scalable pipelines, models, and data services while ensuring data quality, governance, lineage, and documentation standards.
• Translate business logic into data transformations, metadata, and domain-specific rules.
• Serve as the primary liaison between technical teams and business partners, communicating product value, roadmap, and use cases to leadership and cross-functional teams.
• Prioritize incoming requests and balance competing needs across teams.
• Define success metrics and measure product performance and adoption.
• Ensure data products deliver actionable insights and support decision-making across the organization.
• Partner with analytics teams to design dashboards, KPIs, and reporting frameworks.
• Uphold data governance, privacy, and ethical AI standards; ensure compliance with regulatory and organizational data policies.
• Advocate for responsible data use.
• Provide knowledge transfer to support organizational continuity.

Qualifications

• Required
  • 4-7+ years of experience in data management, data analytics, data engineering, or related fields.
  • Demonstrated product leadership skills and ability to work in ambiguity.
  • Strong understanding of data systems including pipelines, warehousing, modeling, metadata, and governance.
  • Proficiency collaborating with data architecture, data engineering, and data science teams.
  • Ability to translate complex technical concepts into business-friendly language.
  • Strong communication, prioritization, and stakeholder management skills.
  • Experience with SQL, data lakes, and data pipelines/ETL.
  • Understanding of large organizational data sharing constraints and data sharing agreements.
• Preferred
  • Experience with analytics tools such as dbt, Looker, Tableau, Power BI, or Google Analytics.
  • Significant experience with Databricks.
  • Familiarity with Java and Python.
  • Background in building internal platforms or developer-facing products.
  • Experience implementing modern data architectures at an organization.
  • Experience in a highly regulated industry performing statistical analysis and reporting.