We are seeking an experienced Data Product Manager to lead significant data transformation initiatives, turning organizational data into scalable, high-value products such as curated datasets, analytics platforms, and data infrastructure.
The Data Product Manager will lead strategy, roadmap, and execution of data initiatives, enabling better decision-making, operational efficiency, and intelligent product experiences. This role will work closely with data engineering, data science, analytics, architecture, and business teams to establish trusted, reusable, governed, and consumable data assets.
Key Responsibilities
Product Strategy & Vision
Define the vision and roadmap for data products, including data platforms, analytics tools, and ML infrastructure.
Identify high-value opportunities by analyzing data landscapes, business needs, and pain points.
Align data product strategy with organizational priorities and long-term data architecture.
Connect data capabilities to business outcomes and prioritize initiatives accordingly.
Coordinate engineering, analytics, and business teams using metrics to guide prioritization and product evolution.
Data Product Development
Lead the end-to-end lifecycle of data products from requirements and design through development, testing, launch, and iteration.
Partner with data engineers and data scientists to develop scalable pipelines, models, and data services.
Ensure data quality, governance, lineage, and documentation standards.
Translate business logic into data transformations, metadata, and domain-specific rules.
Apply knowledge of data architecture, data modeling, and data pipelines.
Ensure data products are reliable, governed, scalable, and reusable.
Stakeholder Management
Act as the primary liaison between technical teams and business stakeholders.
Communicate product value, roadmap, use cases, and progress to leadership and cross-functional teams.
Prioritize requests and balance competing business and technical requirements.
Facilitate collaboration across data engineering, data science, analytics, architecture, and business teams.
Analytics, Insights & Measurement
Define success metrics and measure product performance and adoption.
Ensure data products provide actionable insights and support business decision-making.
Partner with analytics teams to develop dashboards, KPIs, and reporting frameworks.
Governance, Compliance & Ethical Data Use
Support data governance, privacy, and responsible/ethical AI practices.
Ensure compliance with organizational data policies and regulatory requirements.
Promote responsible data use within human services environments.
Provide knowledge transfer and documentation.
Required / Desired Qualifications:
4–7 years of experience in data management, data analytics, data engineering, product management, or related fields.
Demonstrated product leadership skills and ability to work effectively in ambiguous environments.
Strong understanding of data systems, including pipelines, data warehousing, data modeling, metadata, and governance.
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, and stakeholder management skills.
Experience with analytics and visualization tools such as dbt, Looker, Tableau, Power BI, or Google Analytics.
Understanding of enterprise data-sharing constraints and data-sharing agreements.
Strong experience with SQL, data lakes, data pipelines, and ETL.
Significant experience with Databricks.
Familiarity with Java and Python.
Experience building internal platforms or developer-facing products.
Experience implementing modern data architectures within an organization.
Experience working in highly regulated industries involving statistical analysis and reporting.
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