Data Product Manager

• Define the vision and roadmap for data products such as data platforms, analytics tools, and 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
• Connect data capabilities to business outcomes and organize efforts to achieve those outcomes
• Align engineering, analytics, and business teams
• Use metrics to guide prioritization and product evolution
• Lead the end‑to‑end lifecycle of data products, including 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, documentation, reliability, and scalability standards are met
• Translate business logic into data transformations, metadata, and domain‑specific rules
• Serve as the primary liaison between technical teams and business partners
• 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
• Provide knowledge transfer

• 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, including pipelines, warehousing, modeling, metadata, and 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 analytics tools: dbt, Looker, Tableau, Power BI, and 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 implementing modern data architectures at an organization
• Experience in a highly regulated industry performing statistical analysis and reporting
• Must be located within the borders of the United States
• Must be available during regular business hours of 7:00 a.m.–6:00 p.m. Central Time, Monday through Friday

Demonstrates expertise in data product management, including defining vision, aligning strategies with business outcomes, and leading cross‑functional teams. Proficient in data governance, analytics tools, and translating technical concepts for business stakeholders.

• Data Product Management
• Data Governance
• Analytics Tools Proficiency
• SQL and Data Pipelines/ETL
• Product Leadership

• Data Management
• Data Analytics
• Data Engineering
• Data Warehousing
• Data Modeling
• Data Quality
• Data Transformation
• Statistical Analysis
• SQL
• Databricks

• Strong Communication
• Prioritization
• Stakeholder Management
• Collaboration
• Ability to Work in Ambiguity

• Data Architecture
• Data Governance Standards
• Regulatory Compliance
• Data Sharing Agreements
• Ethical AI Standards

• Dbt
• Looker
• Tableau
• Power BI
• Google Analytics