Senior Product Manager, Lumina Data Platform

Accountabilities:

• Define and manage the data sourcing strategy, prioritizing internal systems and third-party providers based on data coverage, cost, licensing, quality, and implementation effort.
• Establish and manage the onboarding process for new data sources, from initial evaluation and provider assessment through ingestion, validation, and production launch.
• Partner with data engineering teams to develop connectors, define schemas, and establish service-level agreements (SLAs) for data sources.
• Create and maintain data contracts and standards covering schemas, freshness, quality, and metadata, including governance processes for changes that may affect downstream consumers.
• Own relationships with internal platform consumers, including product engineering, analytics, data science, Agentic AI, and operations teams.
• Manage incoming requests from internal stakeholders through a transparent prioritization framework, ensuring that consumer feedback informs the product roadmap.
• Define, monitor, and improve platform performance metrics, including source coverage, data freshness, data quality, consumer adoption, and time required to onboard new consumers.
• Maintain the platform roadmap, communicate priorities and delivery timelines, and align data sourcing investments with the needs of internal teams.
• Interview and observe internal users to understand their workflows, identify platform limitations, and uncover opportunities to improve the data consumption experience.
• Write clear product requirements and data contracts, collaborating with engineering teams to estimate, prioritize, and sequence development work.
• Evaluate potential data sources and make informed decisions about which sources to onboard and when.
• Report on platform health, adoption, and progress to leadership and the teams relying on the platform.
• Use AI tools to accelerate source evaluation, requirements development, documentation, consumer feedback analysis, prototyping, and internal support.
• Promote effective AI-assisted workflows across platform teams and share successful practices to improve productivity and delivery.

Requirements:

• At least 5 years of product management experience, including meaningful experience with data, platform, infrastructure, or API products serving internal or technical users.
• Strong understanding of data platforms, including data pipelines, data warehouses and lakes, schemas, data quality, and governance.
• Ability to engage credibly with data engineers and collaborate on technical decisions related to data ingestion, integration, and platform architecture.
• Familiarity with modern cloud-native data environments, including object storage, managed data warehouses, streaming and ELT processes, and orchestration tools.
• Proven ability to treat internal teams as customers, manage competing demands, and drive measurable platform adoption.
• Strong prioritization and decision-making skills, particularly when navigating ambiguous requirements and competing cross-functional requests.
• Experience developing and communicating product roadmaps, making trade-offs explicit, and aligning stakeholders around priorities and delivery expectations.
• Excellent written and verbal communication skills, including the ability to document requirements clearly and communicate technical concepts to diverse audiences.
• An AI-forward mindset, with active use of AI tools to improve productivity, product execution, and team effectiveness.
• Familiarity with real estate, property, leasing, or proptech data is an advantage but not required.
• Experience defining data contracts is desirable.
• Familiarity with data catalogs, data lineage, or self-service analytics tools is a plus.
• SQL proficiency and comfort exploring data directly are beneficial.

Benefits:

• Annual salary range of $94,700–$161,300 USD, depending on location, qualifications, education, training, experience, licensure, and certifications.
• Health, dental, and vision insurance.
• Retirement savings plan with employer matching contributions.
• Paid time off and holidays.
• Professional development opportunities.
• Potential performance-based bonus or other additional incentives, depending on the role and applicable compensation plan.
• Opportunity to influence a foundational data platform supporting teams across product development, analytics, data science, AI, and operations.