Data Product Manager

Title: Data Product Manager

Location: Saint Paul MN (Hybrid)

Duration: 12 Months

Description of Project

The Minnesota Department of Information Technology Services (MNIT) partnering with the Department of Children Youth and Families (DCYF) (collectively State) is seeking one full-time Data Product Manager who will be responsible for supporting significant system changes to turn the organizations data into scalable high value productssuch as curated datasets analytics platforms and data infrastructuresupporting the Whole Family approach. This role will lead efforts across data engineering data science and business strategy that help mature data practices and teams and drive organizational efforts to shift to new data lakes and data curation platforms from current legacy main frame systems.

At a high level the resource will lead the strategy roadmap and execution of data efforts within the Department of Children Youth and Families (DCYF) enabling better decision making operational efficiency and intelligent product experiences. Partnering closely with data engineering data science analytics and business policy and administration the Data Product Manager will facilitate and help drive the path towards trusted reusable governed and consumable data assets across the enterprise. This role requires strong analytical skills deep understanding of data systems and a strong aptitude in translating between technical teams and business understanding throughout the product lifecycle. Product Managers at DCYF guide products through the full lifecyclefrom ideation and design to development deployment monitoring and deprecation.

Sample Tasks

• 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. Uses 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. Skilled in or adept at data architecture modeling and pipelines.
  • Ensures data products are reliable governed and scalable.
• Interested Parties Management:
  • Serve as the primary liaison between technical teams at Minnesota IT Services (MNIT) and business partners across DCYF.
  • 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 by and supported through DCYF and MNIT DCYF.
• Provide knowledge transfer

Desired Qualifications

• Desired 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.