Data Product Manager

About the Role

The Data Product Manager will be responsible for supporting significant system changes to transform the organization's data into scalable, high-value products—such as curated datasets, analytics platforms, and data infrastructure—supporting the Whole Family approach. This role will lead efforts across data engineering, data science, and business strategy to help mature data practices and teams and drive organizational efforts to transition to new data lakes and data curation platforms from current legacy mainframe systems.

Key Responsibilities

• Lead the strategy, roadmap, and execution of data efforts, enabling better decision-making, operational efficiency, and intelligent product experiences.
• Partner closely with data engineering, data science, analytics, and business policy and administration teams to facilitate and drive the path toward trusted, reusable, governed, and consumable data assets across the enterprise.
• Guide products through the full lifecycle—from ideation and design to development, deployment, monitoring, and deprecation.
• Translate between technical teams and business requirements throughout the product lifecycle.

Product Strategy & Vision

• Define the vision and roadmap for data products (e.g., data platforms, analytics tools, 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 the Enterprise Architecture team and various interested parties.
• Connect data capabilities to business outcomes and organize efforts to achieve the business outcomes.
• Align engineering, analytics, and business teams. Use metrics to guide prioritization and product evolution.

Data Product Development

• 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.
• Ensure data quality, governance, lineage, and documentation standards are met.
• Translate business logic into data transformations, metadata, and domain-specific rules.
• Demonstrate skill in or adeptness at data architecture, modeling, and pipelines.
• Ensure data products are reliable, governed, and scalable.

Stakeholder Management

• Serve as the primary liaison between technical teams and business partners across the organization.
• Communicate product value, roadmap, and use cases to leadership and cross-functional teams.
• Prioritize incoming requests and balance competing needs across teams.

Analytics, Insights & Measurement

• Define success metrics and measure product performance and adoption.
• Ensure data products deliver actionable insights and support decision-making.
• Partner with analytics teams to design dashboards, KPIs, and reporting frameworks.

Governance, Compliance & Ethical Data Use

• Uphold data governance, privacy, and ethical AI standards.
• Ensure compliance with regulatory and organizational data policies.
• Advocate for responsible data use across the human services space served and supported by the organization.
• Provide knowledge transfer.

Qualifications

• 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: pipelines, warehousing, modeling, metadata, 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 analytics tools (dbt, Looker, Tableau, Power BI, Google Analytics).
• Understanding of large organizational data-sharing constraints and data-sharing agreements.
• Experience with SQL, data lakes, data, and data pipelines / ETL.
• Significant experience with Databricks.
• Familiarity with Java and Python.
• Background in building internal platforms or developer-facing products.
• Experience in implementing modern data architectures at an organization.
• Experience in a highly regulated industry performing statistical analysis and reporting.

Schedule

• 12-month contract duration (possible extension).
• Hybrid work expected at the organization's offices in St. Paul, MN, or remote.
• Resource must be located within the United States.
• Regular business hours: 7:00 a.m. – 6:00 p.m. Central Time, Monday through Friday.