MN - Data Product Manager (Data Architecture/Engineering) - 3838

Job Title: Data Product Manager (Data Architecture/Engineering)- remote or hybrid

Job ID: 3838

Client: State of Minenesota - MNSite - DCYF

Closing: 9/8/2026, 2:00 PM CDT

Mode of Interview: MS Teams

 

Description of Project

The State (MNIT + DCYF) is hiring a full‑time Data Product Manager to lead major modernization efforts that transform agency data into scalable, high‑value products—such as curated datasets, analytics platforms, and new data‑lake infrastructure replacing legacy mainframe systems.

The role drives the strategy, roadmap, and delivery of DCYF’s data initiatives, enabling better decision‑making, operational efficiency, and improved digital experiences. Working across data engineering, data science, analytics, and business teams, the Data Product Manager ensures the creation of trusted, governed, reusable, and consumable data assets.

This position requires strong analytical skills, deep knowledge of data systems, and the ability to translate between technical and business stakeholders. Product Managers at DCYF own the full product lifecycle—from ideation and design through development, deployment, monitoring, and retirement.

 

Responsibility:

• 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.