Data Product ManagerClient: Minnesota Department of Information Technology Services (MNIT), partnering with the Department of Children, Youth, and Families (DCYF)
Solicitation Number: MNSITE-3838
Job Type: Full-Time
Location: Remote or Hybrid – St. Paul, MN
Office Location: 444 Lafayette Rd N, St. Paul, MN 55155
Work Hours: Monday–Friday, 7:00 AM–6:00 PM Central Time
Interview: Microsoft TeamsPosition OverviewWe are seeking for Minnesota Department of Information Technology Services (MNIT), in partnership with the Department of Children, Youth, and Families (DCYF), an experienced Data Product Manager to lead the strategy, roadmap, and execution of data products and data initiatives supporting DCYF's Whole Family approach.The Data Product Manager will help transform organizational data into scalable, trusted, governed, reusable, and high-value data products, including curated datasets, analytics platforms, data pipelines, and data infrastructure.This role will work at the intersection of data engineering, data science, analytics, enterprise architecture, and business strategy. The successful candidate will translate business needs into actionable data product requirements while helping DCYF transition from legacy mainframe systems toward modern data lakes and data curation platforms.The Product Manager will guide data products through the complete lifecycle—from ideation and requirements through design, development, testing, deployment, monitoring, iteration, and eventual deprecation.Key ResponsibilitiesProduct Strategy & VisionDefine the vision, strategy, and roadmap for data products, including data platforms, analytics tools, and ML infrastructure.Identify high-value data opportunities by evaluating the existing data landscape, business needs, and organizational pain points.Align data product strategy with organizational priorities and long-term data architecture in partnership with Enterprise Architecture and key stakeholders.Connect data capabilities and investments to measurable business outcomes.Align data engineering, analytics, data science, and business teams around common priorities.Use data, metrics, and business outcomes to guide product prioritization and ongoing product evolution.Data Product DevelopmentLead the end-to-end lifecycle of data products, including requirements gathering, design, development, testing, launch, monitoring, and iteration.Partner with data engineers and data scientists to develop scalable data pipelines, models, and data services.Ensure data products meet standards for data quality, governance, lineage, reliability, scalability, and documentation.Translate business logic and requirements into data transformations, metadata, and domain-specific rules.Apply a strong understanding of data architecture, data modeling, data pipelines, and ETL processes.Help ensure data products are reliable, scalable, reusable, and governed.Stakeholder & Cross-Functional ManagementServe as the primary liaison between technical teams at MNIT and business partners across DCYF.Communicate product vision, value, roadmap, priorities, and use cases to leadership and cross-functional teams.Gather and prioritize incoming requests while balancing competing business and technical needs.Facilitate collaboration among data architecture, data engineering, data science, analytics, policy, and administration teams.Translate complex technical concepts into clear, business-friendly language.Analytics, Insights & MeasurementDefine product success metrics and measure product performance, adoption, and business value.Ensure data products provide actionable insights and support effective decision-making.Partner with analytics teams to develop dashboards, KPIs, reporting frameworks, and measurement strategies.Use product and data insights to continuously improve data products and user experiences.Data Governance, Compliance & Responsible Data UseSupport data governance, privacy, compliance, and ethical data-use practices.Ensure data products comply with applicable organizational and regulatory data policies.Promote responsible and ethical use of data within the human services environment supported by DCYF and MNIT.Consider data-sharing constraints, data-sharing agreements, governance requirements, lineage, and documentation throughout the product lifecycle.Knowledge TransferProvide knowledge transfer to relevant MNIT/DCYF teams.Document product requirements, processes, data-related decisions, and relevant technical/business knowledge.Help mature organizational data practices and capabilities.