Data Product Manager

• IT IS 100 % On site position 
  

DESCRIPTION OF PROJECT:

ROLE & RESPONSIBILITIES

• 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
  

Requirements

DESIRED QUALIFICATIONS:

• A bachelor’s degree in computer science, Data Science, Information Systems, Business Analytics, Statistics, or a related quantitative field
  


• 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.
  


• Experience with data modeling, building data pipelines, creating dashboards, or deploying machine learning/AI models into production, 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.
  

• SQL (Mandatory): Essential for querying databases, inspecting data quality, and validating models.
  


• Python: Widely used for data manipulation, exploratory data analysis (pandas/NumPy), and scripting.
  


• Visualization: Tableau, Power BI, Looker, Metabase.