Data Product Manager
The Data Product Manager at Confidential Client is responsible for managing data as a product throughout its lifecycle, bridging business, data engineering, and AI teams to ensure high-quality, governed data products fit for analytics and automation. This role involves defining product vision, translating business needs into Agile deliverables, collaborating on data platform integration, and enforcing data quality and governance standards in regulated environments. The position requires strong skills in SQL, data platforms like Databricks and Snowflake, Agile methodologies, and experience with AI/ML data products.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, IT Services and IT Consulting.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
Role overview
Confidential Client is seeking a Data Product Manager (also listed as Data Product Analyst) to own data-as-a-product across its lifecycle — from source systems through data platforms (Databricks, Snowflake), into AI/ML pipelines, and into production and UAT. This contract role partners with business stakeholders, data engineering, and AI teams to define, govern, validate, and measure data products used for analytics, reporting, and automation.
Key responsibilities
- Partner with product and business stakeholders to discover data product opportunities and define product vision, scope, and success metrics
- Conduct user discovery, stakeholder interviews, and journey mapping to identify gaps and prioritize use cases
- Translate business needs into epics, features, and user stories with clear acceptance criteria
- Own and prioritize the data product backlog; support sprint planning, reviews, and UAT in Agile/Scrum teams
- Collaborate with Data Engineering to onboard internal systems (ERP/SCM/operational sources) into Databricks/Snowflake pipelines
- Work with AI/ML teams to define data inputs/features and validate post‑processing logic and model outputs
- Define and enforce data quality rules, validation checks, SLAs, and monitoring across processing and AI layers
- Establish and maintain data catalog, business glossary, metadata, and lineage to support governance and discoverability
- Track product metrics (time, cost, quality, adoption) and drive continuous improvements based on usage and stakeholder feedback
Required qualifications
- Proven experience in Data Product Analyst, Data Product Manager, Product-centric data roles, or similar
- Strong SQL proficiency for validation, testing, and ad-hoc analysis
- Experience with modern data platforms and ecosystems (Databricks, Snowflake, cloud data architectures)
- Practical experience with data pipelines, large-scale datasets, and ETL/ELT workflows
- Familiarity with Agile/Scrum delivery and translating business requirements into actionable backlog items
- Experience with metadata management, data cataloging, lineage, and data onboarding processes
- Comfortable working in control‑heavy or regulated environments with attention to entitlements and governance workflows
- Bachelor’s degree or equivalent experience
Nice-to-have / Preferred
- Exposure to AI/ML-enabled data products and validating AI outputs from business/data perspectives
- Domain experience in enterprise operations, HR/talent, or financial services
- Experience with enterprise ERP or operational datasets
- Python experience for lightweight data validation or prototyping
- Background in data quality tooling and data governance platforms
Working details
- Employment type: CONTRACTOR
- Location: Wilmington, DE (on-site / client site as required)
- Work authorization: Applicants must be legally authorized to work in the United States.
- Reasonable accommodations: Confidential Client and Careertakes will provide reasonable accommodations during the hiring process upon request.
What we value
- Strong communication and stakeholder management skills
- Product mindset with attention to data quality, documentation, and observability
- Ability to balance technical detail with business outcomes
- Bias for structured discovery, measurement, and iterative improvement
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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