What are the responsibilities and job description for the Data Product Owner position at TheStaffed?
Our client is seeking an experienced Data Product Owner to own the end-to-end lifecycle of multiple enterprise data products and drive adoption across the organization. This role combines strategic product management with hands-on data analysis, requiring deep collaboration between business stakeholders and technical engineering teams.
Responsibilities & Qualifications
- Own end-to-end product lifecycle for multiple enterprise data products, including roadmap definition, prioritization, and communication
- Develop and manage detailed product backlogs, user stories, and success metrics (KPIs, adoption, data quality benchmarks)
- Serve as primary liaison between business users, stakeholders (Sales, Strategy, Finance, Operations), and data engineering teams
- Conduct discovery sessions, workshops, and user interviews to understand requirements and drive product strategy
- Perform hands-on data analysis including profiling, anomaly detection, validation, and quality assessments
- Define and enforce data governance frameworks, quality standards, and metadata management practices
- Collaborate with data engineers on technical design decisions and evaluate data platforms, tools, and vendors
- Champion data literacy and best practices across business teams while managing dependencies, risks, and cross-functional blockers
Requirements
- 8–10 years of professional experience in data product management or data product ownership
- Strong expertise in enterprise data platforms (Snowflake, Databricks) and SQL for data analysis and querying
- Demonstrated experience in data governance, data quality management, metadata management, and data lineage
- Hands-on proficiency with data analysis tools and comfortable with technical problem-solving
- Experience with project management tools (Jira, Confluence) and agile methodologies
- Financial services or enterprise software background preferred
- Excellent communication and stakeholder management skills, with ability to translate between technical and business contexts
- Strong analytical mindset with proven ability to define metrics, track KPIs, and drive data-informed decisions