Data Product Manager – Enterprise AI & Data Strategy

Kapitus, Inc.; Oregon; Hybrid; USD 96.000 - 154.000; Vollzeit

Zusammenfassung

Kapitus is seeking a Data Product Manager to own data products end-to-end, bridging business needs with data engineering, governance, and customer teams. You will translate business problems into measurable products and define acceptance criteria.

This is a product-discipline role (not hands-on engineering). You will collaborate with U.S. and India teams, drive metrics, and supervise retirement of legacy reports, aiming to turn data into decisions.

Qualifikationen

• 5+ years in data product management, product ownership, or customer-facing data & analytics roles in a data-intensive environment.
• Bachelor's degree in Business, Analytics, Computer Science, Information Systems, or a related field, or equivalent practical experience.
• Business vertical experience — required. 3+ of those years working with data in small business lending, commercial or consumer credit, merchant financing, payments, or closely adjacent financial services.
• Command of the data product management discipline — the difference between running a product and running a project; value propositions and value hypotheses; business cases; stage-gated life cycle management from ideation through build, launch, operation, scaling, and retirement.
• Outcome orientation — you measure products by business outcomes, not technical output: defining outcome-driven metrics with stakeholders, tracking product KPIs (adoption, usage, quality, service levels, cost-to-serve), producing usage reporting and portfolio scorecards, and telling credible value stories.
• Excellent communication and stakeholder management — the defining skill of this role. You can run a requirements workshop in the morning, present to executives or customers in the afternoon, and write specifications both audiences trust.
• A portfolio of real product artifacts — you have personally authored the working documents of this discipline: product one-pagers and business cases with quantified ROI, PRDs with acceptance criteria, data contract and semantic specifications, metric dictionaries with agreed formulas and owners, adoption and usage dashboards, and sunset/retirement plans. Expect to walk us through examples you wrote.
• Requirements-to-build capability — proven ability to gather, structure, and prioritize business requirements into PRDs and buildable product specifications, validated with consumers at each stage.
• Architecture literacy, not hands-on engineering — you understand modern data platform concepts (cloud warehouse, layered architecture, data contracts, semantic definitions, BI and API serving) well enough to link requirements to our architecture and converse credibly with engineers on Snowflake, dbt, Tableau, and AWS — without building it yourself.
• Cross-functional, cross-geography delivery experience — Agile/Scrum, distributed teams, strong attention to detail, and excellent project management.

Aufgaben

• Identify business problems worth solving with data; clarify each product's value proposition — utility, decision enabler, or driver of new business value — and quantify expected impact before anything is built.
• Define outcome-driven metrics that link each product to business goals (revenue growth, cost, risk, customer experience), alongside standardized product KPIs — adoption, usage, quality, service levels, cost-to-serve — maintained in a metrics dictionary with agreed formulas and owners; avoid vanity metrics that measure activity instead of value.
• Own usage reporting and portfolio transparency: scorecards, value stories co-created with stakeholders, and regular reviews informing invest, pivot, or retire decisions.
• Own retirement: sunset policies, end-of-life roadmaps, and structured decommissioning for products — and legacy workflows — that fail to sustain business value.
• Elicit requirements through stakeholder interviews, focus groups, and customer journey mapping; translate vague, ill-defined needs into well-defined, testable product requirements with clear acceptance criteria.
• Turn requirements into product definitions engineering can build: named owners, defined consumers, data contracts, certified semantic definitions, quality thresholds, and service levels.
• Link every requirement to our platform architecture — layered data foundation, governed core entities, certified semantics, and serving channels (BI, APIs, ML, AI) — so products are built on the platform, not beside it.
• Champion prototyping and iteration: confirm value with consumers at every development stage rather than specifying once and walking away.
• Serve as the connective tissue between business requirements, data engineering, governance, and customer-facing teams, translating in both directions so needs and delivery stay aligned.
• Engage business and technical stakeholders to communicate progress, surface trade-offs, and present recommendations clearly to technical, non-technical, and customer audiences.
• Serve as the primary coordination point between U.S. and India-based teams, ensuring alignment on priorities, requirements, handoffs, and delivery timelines.
• Partner with Data Engineering on backlog priorities and sequencing, and with Data Governance on definitions, standards, quality, lineage, and appropriate usage — in an Agile/Scrum environment.

Kenntnisse

Data product management

Stakeholder management

Agile/Scrum

Requirements gathering

Business problem framing

Ausbildung

Bachelor's degree in Business, Analytics, CS, IS

Tools

Snowflake

dbt

Tableau

AWS

Jobbeschreibung

Kapitus is seeking a Data Product Manager to own data products end-to-end, bridging business needs with data engineering, governance, and customer teams. You will translate business problems into measurable products and define acceptance criteria.

This is a product-discipline role (not hands-on engineering). You will collaborate with U.S. and India teams, drive metrics, and supervise retirement of legacy reports, aiming to turn data into decisions.