Data Product Manager

Themesoft Inc; Wilmington (DE); On-site; USD 110,000 - 160,000; Full time

Job summary

Themesoft Inc is seeking a Data Product Manager/Data Product Analyst to own data as a product across its lifecycle—from source systems through Databricks and Snowflake, into AI/ML pipelines, and into production. You will bridge business, data engineering, and AI teams to ensure data products are well‑defined, governed, high quality, and fit for analytics.

Responsibilities include discovering data opportunities, defining product vision, managing the backlog, and collaborating with ERP/operational

Qualifications

• Experience in data product analyst, product analyst, or product‑centric data roles.
• Strong understanding of the product development lifecycle.
• Proven ability to translate business needs into epics, features, and user stories.
• Experience working in Agile / Scrum environments.

Responsibilities

• Partner with Product Managers to identify and define data product opportunities aligned to customer and business needs.
• Conduct user discovery, stakeholder interviews, and journey mapping to identify data gaps and opportunities.
• Define product vision, scope, and success metrics for assigned data products.
• Translate business needs into product requirements, epics, features, and user stories with clear acceptance criteria.
• Own and manage a prioritized data product backlog and support sprint planning, reviews, and UAT in Agile/Scrum teams.
• Collaborate with Data Engineering to onboard new data sources and validate AI inputs/outputs.
• Ensure data products meet analytics, reporting, and automation requirements.

Skills

Data product roles

Product development lifecycle

Epics & user stories

Agile / Scrum

Tools

Databricks

Snowflake

SQL

Job description

Position: Data Product Manager/ Data Product Analyst

Job Description

The Data Product Analyst/ Data Product Manager owns data as a product across its lifecycle - from source systems through data platforms (Databricks), into AI/ML pipelines, and finally to production and UAT. This role bridges business, data engineering, and AI teams, ensuring data products are well‑defined, governed, high‑quality, and fit for analytics and automation use cases.

Product & Analysis Skills

• Experience in Data Product Analyst, Product Analyst, or Product‑centric Data roles
• Strong understanding of the product development lifecycle
• Proven ability to translate business needs into epics, features, and user stories
• Experience working in Agile / Scrum environments

Data & Platform Skills

• Strong SQL proficiency for:
• Data validation
• Testing
• Ad‑hoc analysis
• Hands‑on understanding of:
• Working knowledge of modern data platforms:
• Databricks
• Snowflake

Governance & Compliance Skills

• Experience with:
• Data onboarding
• Metadata management
• Data cataloging and lineage
• Familiarity with control‑heavy / regulated environments
• Understanding of entitlements, data quality tooling, and governance workflows
• Experience validating AI outputs from a business and data perspective
• Domain experience in enterprise operations, HR/Talent, or financial services
• Experience working with enterprise ERP or operational datasets
• Python programming knowledge experience

Core Responsibilities

Data Product Ownership & Discovery

• Partner with Product Managers to identify and define data product opportunities aligned to customer and business needs
• Conduct user discovery, stakeholder interviews, and journey mapping to identify data gaps, pain points, and opportunities
• Define product vision, scope, and success metrics for assigned data products

Requirements & Agile Delivery

• Translate business needs into:
• Product requirements
• Epics, features, and user stories
• Clear acceptance criteria
• Own and manage a prioritized data product backlog
• Support sprint planning, reviews, and UAT in Agile/Scrum teams

Data Platform & AI Enablement

• Collaborate with Data Engineering to onboard new data sources from internal systems (e.g., ERP / SCM platforms)
• Work with AI/ML teams to:
• Define data inputs and features
• Validate post‑processing logic and outputs
• Ensure data products meet analytics, reporting, and automation requirements

Data Quality, Governance & Lifecycle

• Define and enforce:
• Data quality rules
• SLAs across processing and AI layers
• Establish and maintain:
• Business glossary
• Metadata and lineage
• Ensure compliance with enterprise governance standards in regulated environments

Measurement & Continuous Improvement

• Track and analyze product metrics including:
• Time
• Cost
• Quality
• Adoption and usage
• Drive continuous improvement through stakeholder feedback and usage insights

Work Authorization

Applicants must be legally authorized to work in the United States.

Themesoft Inc is an Equal Employment Opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local law.

Regards

Talent Acquisition Group - Strategic Recruitment Manager