Data Product Manager
Description of Project
Our client is seeking a full-time Data Product Manager to lead data product strategy and support a significant modernization of its data environment. This individual will be responsible for turning organizational data into trusted, reusable, and high-value products, including data platforms, curated datasets, analytics tools, and data infrastructure.
The Data Product Manager will lead initiatives spanning data engineering, data science, analytics, and business strategy, helping drive the transition from legacy systems to modern data lakes, data platforms, and data curation solutions.
This role will own the strategy, roadmap, and execution of data product initiatives from ideation through development, launch, monitoring, and continuous improvement. The successful candidate will work closely with data engineering, data science, analytics, architecture, and business teams to identify high-value opportunities, translate business needs into technical requirements, and ensure data products deliver measurable business outcomes.
The ideal candidate combines strong product leadership with a solid technical understanding of data architecture, modeling, pipelines, governance, and analytics. They should be comfortable operating in an ambiguous environment, balancing competing priorities, and translating complex technical concepts into clear business language.
Key Responsibilities
Product Strategy & Vision
- Define the vision, strategy, and roadmap for data products, including data platforms, analytics tools, and machine learning infrastructure.
- Identify high-value 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.
- Connect data capabilities to measurable business outcomes and organize initiatives around those outcomes.
- Align engineering, analytics, architecture, and business teams around product priorities and objectives.
- Use metrics and business outcomes to guide prioritization and product evolution.
Data Product Development
- Lead the end-to-end lifecycle of data products, including requirements, design, development, testing, launch, and ongoing iteration.
- Partner with data engineers and data scientists to develop scalable data pipelines, models, and data services.
- Translate business logic into data transformations, metadata, and domain-specific rules.
- Apply knowledge of data architecture, data modeling, pipelines, and modern data platforms to guide product development.
- Ensure data products are reliable, well-documented, governed, and scalable.
- Establish and maintain standards for data quality, governance, lineage, and documentation.
Stakeholder & Cross-Functional Management
- Serve as the primary liaison between technical teams and business stakeholders.
- Communicate product value, roadmaps, use cases, and priorities to leadership and cross-functional teams.
- Prioritize incoming requests and balance competing needs across teams.
- Facilitate collaboration between technical and business teams to ensure solutions align with organizational needs.
- Provide knowledge transfer and help build organizational understanding of data products and capabilities.
Analytics, Insights & Measurement
- Define success metrics and measure product performance, adoption, and business impact.
- Ensure data products provide actionable insights and support informed decision-making.
- Partner with analytics teams to develop dashboards, KPIs, and reporting frameworks.
- Use data and performance metrics to continuously evaluate and improve products.
Governance, Compliance & Responsible Data Use
- Promote strong data governance, privacy, security, and responsible data-use practices.
- Ensure data products comply with applicable regulatory and organizational policies.
- Understand data-sharing constraints, data-sharing agreements, and requirements associated with large organizational data environments.
- Advocate for responsible and ethical use of data, particularly within highly regulated environments.
Desired Qualifications
- 4–7 years of experience in data management, data analytics, data engineering, product management, or a related field.
- Demonstrated product leadership experience with the ability to operate effectively in ambiguous environments.
- Strong understanding of data systems, including data pipelines, data warehousing, data modeling, metadata, and governance.
- Experience collaborating with data architecture, data engineering, and data science teams.
- Ability to translate complex technical concepts into clear, business-friendly language.
- Strong communication, prioritization, problem-solving, and stakeholder management skills.
- Experience with analytics and data tools such as dbt, Looker, Tableau, Power BI, or Google Analytics.
- Experience with SQL, data lakes, ETL processes, and modern data pipelines.
- Significant hands-on experience or strong working knowledge of Databricks.
- Familiarity with Java and Python.
- Experience building internal platforms or developer-facing products.
- Experience implementing or supporting modern data architectures within an organization.
- Experience working within highly regulated industries, particularly in environments requiring statistical analysis, reporting, governance, or complex data-sharing considerations.
Work Arrangement
The position is expected to be performed remotely or in a hybrid capacity. The resource must be located within the United States and be available during regular business hours of 7:00 a.m. – 6:00 p.m. Central Time, Monday through Friday.
Project Schedule
- Anticipated Start Date: September 2026
- Anticipated End Date: August 2027
- Extension: The engagement may be extended based on project needs.