Data Product Manager

Integres, LLC is a Service-Disabled Veteran Owned Small Business (SDVOSB) which was established to provide high quality, insightful, agile information technology-based solutions to its customers. Integrity is a foundational element of everything we strive to do. We seek to develop solutions which respond to the evolving challenges that today’s organizations face using our own unique combination of industry best practices, and evolving techniques and technologies. We started Integres with the intent of building "a company with a soul". As such, we take a servant-leadership approach as the long-term strategy for our success. We are cultivating a corporate family culture which demands excellence and accountability while putting a premium on work/life balance. We empower and support our employees to contribute to achieving our corporate goals by interacting with our customers as true partners, rather than treating their engagement as just another job. We seek to be good corporate citizens and encourage and promote employee participation in community and volunteer work.

Data Product Manager

Client: Minnesota Department of Information Technology Services (MNIT), partnering with the Department of Children, Youth, and Families (DCYF)
Solicitation Number: MNSITE-3838
Job Type: Full-Time
Location: Remote or Hybrid – St. Paul, MN
Office Location: 444 Lafayette Rd N, St. Paul, MN 55155
Work Hours: Monday–Friday, 7:00 AM–6:00 PM Central Time
Interview: Microsoft Teams

Position Overview

We are seeking for Minnesota Department of Information Technology Services (MNIT), in partnership with the Department of Children, Youth, and Families (DCYF), an experienced Data Product Manager to lead the strategy, roadmap, and execution of data products and data initiatives supporting DCYF's Whole Family approach.

The Data Product Manager will help transform organizational data into scalable, trusted, governed, reusable, and high-value data products, including curated datasets, analytics platforms, data pipelines, and data infrastructure.

This role will work at the intersection of data engineering, data science, analytics, enterprise architecture, and business strategy. The successful candidate will translate business needs into actionable data product requirements while helping DCYF transition from legacy mainframe systems toward modern data lakes and data curation platforms.

The Product Manager will guide data products through the complete lifecycle—from ideation and requirements through design, development, testing, deployment, monitoring, iteration, and eventual deprecation.

Key Responsibilities

Product Strategy & Vision

• Define the vision, strategy, and roadmap for data products, including data platforms, analytics tools, and ML infrastructure.
• Identify high-value data opportunities by evaluating the existing data landscape, business needs, and organizational pain points.
• Align data product strategy with organizational priorities and long-term data architecture in partnership with Enterprise Architecture and key stakeholders.
• Connect data capabilities and investments to measurable business outcomes.
• Align data engineering, analytics, data science, and business teams around common priorities.
• Use data, metrics, and business outcomes to guide product prioritization and ongoing product evolution.

Data Product Development

• Lead the end-to-end lifecycle of data products, including requirements gathering, design, development, testing, launch, monitoring, and iteration.
• Partner with data engineers and data scientists to develop scalable data pipelines, models, and data services.
• Ensure data products meet standards for data quality, governance, lineage, reliability, scalability, and documentation.
• Translate business logic and requirements into data transformations, metadata, and domain-specific rules.
• Apply a strong understanding of data architecture, data modeling, data pipelines, and ETL processes.
• Help ensure data products are reliable, scalable, reusable, and governed.

Stakeholder & Cross-Functional Management

• Serve as the primary liaison between technical teams at MNIT and business partners across DCYF.
• Communicate product vision, value, roadmap, priorities, and use cases to leadership and cross-functional teams.
• Gather and prioritize incoming requests while balancing competing business and technical needs.
• Facilitate collaboration among data architecture, data engineering, data science, analytics, policy, and administration teams.
• Translate complex technical concepts into clear, business-friendly language.

Analytics, Insights & Measurement

• Define product success metrics and measure product performance, adoption, and business value.
• Ensure data products provide actionable insights and support effective decision-making.
• Partner with analytics teams to develop dashboards, KPIs, reporting frameworks, and measurement strategies.
• Use product and data insights to continuously improve data products and user experiences.

Data Governance, Compliance & Responsible Data Use

• Support data governance, privacy, compliance, and ethical data-use practices.
• Ensure data products comply with applicable organizational and regulatory data policies.
• Promote responsible and ethical use of data within the human services environment supported by DCYF and MNIT.
• Consider data-sharing constraints, data-sharing agreements, governance requirements, lineage, and documentation throughout the product lifecycle.

Knowledge Transfer

• Provide knowledge transfer to relevant MNIT/DCYF teams.
• Document product requirements, processes, data-related decisions, and relevant technical/business knowledge.
• Help mature organizational data practices and capabilities.

• 4–7 years of experience in data management, data analytics, data engineering, product management, or a related field.
• Demonstrated product leadership experience and the ability to work effectively in ambiguous environments.
• Strong understanding of:
  • Data pipelines
  • Data warehousing
  • Data modeling
  • Metadata
  • Data governance
  • Data lakes
  • ETL/data integration
• Experience collaborating with Data Architecture, Data Engineering, and Data Science teams.
• Strong ability to translate complex technical concepts into business-friendly language.
• Excellent communication, prioritization, stakeholder management, and cross-functional collaboration skills.
• Experience with analytics and data tools such as dbt, Looker, Tableau, Power BI, or Google Analytics.
• Understanding of organizational data-sharing constraints and data-sharing agreements.
• Strong experience with SQL.
• Experience working with data lakes and data pipelines/ETL.
• Significant experience with Databricks.
• Familiarity with Python and Java.
• Experience building internal platforms or developer-facing products.
• Experience implementing modern data architectures within an organization.
• Experience working in a highly regulated industry, including statistical analysis and reporting.

Integres offers competitive salaries bolstered by a comprehensive benefits package, which provides safety and security for our employees and their families.  Our generous benefits package includes:

• Healthcare and Insurance: medical, dental, vision, short and long-term disability protection, basic life and AD&D insurance
• 401(k) Savings Plan
• Accrued Paid Time Off (PTO)
• Employee Recognition and Rewards
• Employee Referral Bonuses

Integres is an equal opportunity affirmative-action employer.  We encourage Minority/Female/Protected Veteran/Disabled applicants to apply.  Integres, LLC proactively fulfills its role as an equal opportunity employer.  We do not discriminate against any employee or applicant for employment because of race, color, sex, religion, age, sexual orientation, gender identity and expression, national origin, marital status, physical or mental disability, status as a Disabled Veteran, Recently Separated Veteran, Active Duty Wartime, or Campaign Badge Veteran, Armed Forces services Medal, or any other characteristic protected by law.

All your information will be kept confidential according to EEO guidelines.