Data Product Manager — Enterprise Data Platforms

HighCloud Solutions; Saint Paul (MN); On-site; USD 120,000 - 170,000; Full time

Job summary

MNIT in partnership with DCYF seeks a Data Product Manager to lead data product strategy and execution. You will coordinate data engineering, data science, and business policy to deliver scalable, governed data assets and analytics platforms across the enterprise.

You will translate business needs into data-driven solutions, define roadmaps, and measure impact with dashboards and KPIs, supporting better decision-making and efficiency in a highly regulated human services context.

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.

Responsibilities

• 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.
• 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.
• Serve as the primary liaison between technical teams at 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.
• 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.
• 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 MNIT and DCYF.
• Provide knowledge transfer

Skills

Data governance

Data analysis

Stakeholder mgmt

SQL

Databricks

Python

Java

Data pipelines

Tools

dbt

Looker

Tableau

Power BI

Google Analytics

Job description

MNIT in partnership with DCYF seeks a Data Product Manager to lead data product strategy and execution. You will coordinate data engineering, data science, and business policy to deliver scalable, governed data assets and analytics platforms across the enterprise.

You will translate business needs into data-driven solutions, define roadmaps, and measure impact with dashboards and KPIs, supporting better decision-making and efficiency in a highly regulated human services context.