Find & Apply For Landscaping / Grounds Supervisor Jobs in Saint Paul Park, Minnesota

Client is recruiting a Data Product Manager to support State Project. This individual will lead the strategy, roadmap, and delivery of scalable data products that help transform legacy mainframe data into trusted datasets, analytics platforms, and modern data infrastructure. You will work at the intersection of product management, data engineering, data science, architecture, and public-sector program teams. The role calls for someone who can navigate ambiguity, translate between technical and business stakeholders, and turn complex data needs into governed, reusable products that improve decision-making and operational efficiency. What You'll Do Define the vision, strategy, roadmap, and success measures for enterprise data products. Identify high-value opportunities by evaluating business needs, user pain points, and the existing data landscape. Lead the product lifecycle from discovery and requirements through design, development, testing, launch, iteration, and retirement. Partner with data engineers and data scientists to develop scalable pipelines, models, data services, curated datasets, and analytics capabilities. Translate business rules into data transformations, metadata, and domain-specific requirements. Establish expectations for data quality, governance, lineage, reliability, scalability, and documentation. Serve as a primary liaison between MNIT technical teams and DCYF business, policy, and administrative stakeholders. Prioritize competing requests and align product investments with organizational outcomes and long-term architecture. Define KPIs, dashboards, adoption measures, and reporting frameworks. Support responsible data use, privacy, regulatory compliance, and ethical AI practices in a human-services environment. Provide documentation and knowledge transfer throughout the engagement. What We're Looking For Approximately 4 7 years of experience in data management, analytics, data engineering, data product management, or a related field. Demonstrated product leadership and the ability to make progress in an ambiguous, multi-stakeholder environment. Strong understanding of data pipelines, ETL, warehousing, lakes, modeling, metadata, lineage, and governance. Experience collaborating with data architecture, data engineering, data science, analytics, and business teams. Strong communication, prioritization, and stakeholder-management skills. Ability to explain complex technical concepts in clear, business-friendly language. Hands-on experience with SQL and significant experience with Databricks. Experience with tools such as dbt, Looker, Tableau, Power BI, or Google Analytics. Familiarity with Python and Java. Experience building internal platforms, developer-facing products, or modern data architectures. Understanding of enterprise data-sharing constraints and data-sharing agreements. Experience working with statistical reporting or data products in a regulated environment is strongly preferred. ||