The Role
Leads the strategy, roadmap, and full lifecycle delivery of data products, including curated datasets, analytics platforms, pipelines, and data infrastructure. Partners with engineering, data science, analytics, architecture, and business teams to define requirements, ensure scalability, quality, governance, privacy, and compliance, and translate technical concepts into business outcomes. Establishes metrics, dashboards, and reporting frameworks while managing stakeholders, prioritizing requests, and supporting modernization from legacy mainframe systems to data lakes and modern curation platforms.
Summary Generated by Built In
PLEASE NOTE:
- IT IS 100 % On site position
DESCRIPTION
OF PROJECT:
The Client ("MNIT") partnering
with the Department of Children, Youth, and Families ("DCYF")
(collectively "State") is seeking one full-time Data Product Manager who will be responsible for
supporting significant system changes to turn the organization’s data into
scalable, high value products—such as curated datasets, analytics platforms,
and data infrastructure- supporting the Whole Family approach. This role will lead efforts across data
engineering, data science, and business strategy that help mature data
practices and teams and drive organizational efforts to shift to new data lakes
and data curation platforms from current legacy main frame systems.
At a high level,
the resource will lead the strategy, roadmap, and execution of data efforts
within the Department of Children, Youth, and Families (DCYF), enabling better
decision making, operational efficiency, and intelligent product experiences.
Partnering closely with data engineering, data science, analytics, and business
policy and administration, the Data Product Manager will facilitate and help
drive the path towards trusted, reusable, governed, and consumable data assets
across the enterprise.This role requires strong analytical skills, deep understanding of data systems, and a strong aptitude in translating between technical teams and business understanding, throughout the product lifecycle. Product Managers at DCYF guide products through the full lifecycle—from ideation and design to development, deployment, monitoring, and deprecation.
ROLE
& RESPONSIBILITIES
Data Product Manager focus on data architecture, pipeline scalability, data quality, and analytical utility
- 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.
Hands on experience
- 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.
Skills Required
- Bachelor’s degree in computer science, data science, information systems, business analytics, statistics, or a related quantitative field
- 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, data pipelines, dashboards, machine learning or AI model deployment, data warehousing, metadata, and data governance
- Experience 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 dbt, Looker, Tableau, Power BI, or Google Analytics
- Understanding of organizational data-sharing constraints and data-sharing agreements
- Experience with SQL, data lakes, data pipelines, and ETL
- Significant experience with Databricks
- Familiarity with Java and Python
- Background building internal platforms or developer-facing products
- Experience implementing modern data architectures
- Experience in a highly regulated industry performing statistical analysis and reporting
- Hands-on SQL experience
- Hands-on Python experience for data manipulation, exploratory data analysis, and scripting
- Experience with Tableau, Power BI, Looker, or Metabase
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The Company
What We Do
Omm IT Solutions is a leading provider of IT consulting, analysis, and advisory services, specializing in delivering technical solutions for federal and state government agencies. Their offerings include application development, cybersecurity services, cloud advisory, network modernization, and data analytics.
