Data Product Manager

Job Title: Data Product Manager

Location: Remote

Duration: 6+ Months

Job Description

• 5+ 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.

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.