Senior Product Manager - Data Platform & Analytics

CLEAR DEMAND Inc.; Oregon; Hybrid; USD 140,000 - 180,000; Full time

Job summary

CLEAR DEMAND Inc. is seeking an experienced Data Product Manager to own the data platform, backend data architecture, and foundational data capabilities powering our Analytics and Intelligence solutions in a fast-paced SaaS environment.

You will define requirements for data structures, pipelines, and data services to enable scalable analytics, and partner with Engineering, Data Science, Analytics, and Product teams to translate business needs into robust data product requirements.

Qualifications

• 5-8+ years in Product Management with data platform focus.
• Strong understanding of data architecture, modeling, and pipelines.
• Experience delivering data products for BI, analytics, or AI/ML.

Responsibilities

• Own product strategy, roadmap, and delivery of data platform capabilities.
• Define backend data structures, data models, pipelines, and data services for scalable analytics.
• Collaborate with Engineering, Data Science, Analytics, and Product teams to define data product requirements.
• Drive data standardization, quality, governance, accessibility, and reusability across product lines.
• Define success metrics for reliability, performance, scalability, and business value.
• Balance long-term platform investments with immediate customer needs.

Skills

Product management

Data platforms

Data architecture

Data modeling

ETL/ELT pipelines

Cloud data infra

APIs

Stakeholder management

Agile execution

Roadmap prioritization

Tools

GCP

Data warehouses

Lakehouses

APIs

Job description

Role Overview

ClearDemand is seeking an experienced, technically strong Data Product Manager to own the data platform, backend data architecture, and foundational data capabilities powering our Analytics and Intelligence solutions. This role requires a strong combination of product management expertise, data platform knowledge, and the ability to translate complex business and analytical requirements into scalable, reliable data products in a fast-paced SaaS environment.

Key Responsibilities

• Own the product strategy, roadmap, and delivery of foundational data platform capabilities supporting Analytics, Reporting, and AI/ML solutions.
• Define requirements for backend data structures, data models, pipelines, and data services to enable scalable, consistent, and performant analytics.
• Partner closely with Engineering, Data Science, Analytics, and Product teams to translate business needs into well-defined data product requirements.
• Drive data standardization, quality, governance, accessibility, and reusability across product lines.
• Define clear success metrics for data reliability, performance, scalability, cost efficiency, and business value.
• Balance long-term platform investments with immediate product and customer needs, managing priorities and technical dependencies.

Required Experience & Skills

• 5-8+ years of Product Management experience, with significant exposure to data platforms, analytics, or enterprise data products.
• Strong technical understanding of data architecture, data modeling, ETL/ELT pipelines, data warehouses, lakehouses, APIs, and cloud data infrastructure.
• Experience defining data products that support business intelligence, advanced analytics, and AI/ML applications.
• Familiarity with cloud platforms such as GCP and modern data technologies.
• Ability to collaborate effectively with Data Engineering and Architecture teams, understanding technical trade-offs without necessarily being a hands-on engineer.
• Strong product discovery, requirements definition, roadmap prioritization, stakeholder management, and agile execution skills.
• Retail, pricing, promotions, or merchandising data domain experience is highly desirable.
• Ability to thrive in fast-paced, ambiguous environments, demonstrating ownership, adaptability, strong problem-solving skills, and a bias for action.

Ideal Candidate

A technically fluent, outcome-driven Product Manager who understands how to turn complex backend data infrastructure into scalable, reusable data products. Someone who can bridge business, analytics, and engineering needs, establish strong data foundations, and accelerate the delivery of customer-facing analytics and intelligence capabilities.