Job Description

• Product Strategy & Vision: o Define the vision and roadmap for data products (e.g., data platforms, analytics tools, ML infrastructure).

o Identify high value opportunities by investigating the data landscape, pain points, and business needs.

o Align data product strategy with organizational priorities and long-term data architecture, in partnership with the Enterprise Architecture team and various interested parties.

o Connect data capabilities to business outcomes and organize efforts to achieve the business outcomes.

o Align engineering, analytics, and business teams. Uses metrics to guide prioritization and product evolution.

• Data Product Development:

o Lead the end-to-end lifecycle of data products: requirements, design, development, testing, launch, and iteration.

o 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.

o Translate business logic into data transformations, metadata, and domain specific rules. Skilled in or adept at data architecture, modeling, and pipelines.

o Ensures data products are reliable, governed, and scalable.

• Interested Parties Management:

o Serve as the primary liaison between technical teams at Minnesota IT Services (MNIT) and business partners across DCYF.

o Communicate product value, roadmap, and use cases to leadership and cross-functional teams.

o Prioritize incoming requests and balance competing needs across teams.

• Analytics, Insights & Measurement:

o Define success metrics and measure product performance and adoption.

o Ensure data products deliver actionable insights and support decision making.

o Partner with analytics teams to design dashboards, KPIs, and reporting frameworks.

• Governance, Compliance & Ethical Data Use:

o Uphold data governance, privacy, and ethical AI standards.

o Ensure compliance with regulatory and organizational data policies.

o 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.