Senior Product Manager - Data Quality and Observability

About Us:

At , data drives our decisions. Technology is at our core. And innovation is everywhere. But our company is more than datasets, lines of code or A/B tests. We’re the thrill of the first night in a new place. The excitement of the next morning. The friends you encounter. The journeys you take. The sights you see. And the memories you make.

Through our products, partners and people, we make it easier for everyone to experience the world.

The Data Foundations product group comprises a suite of horizontal products / services that support both data producers and consumers in getting the most out of the platform, supporting both target segments with foundational capabilities expected out of an enterprise grade data & ML platform. Platform products like distributed compute, compute marketplace, distributed storage, Identity and Access Management, Discovery & Lineage, Privacy make up the data foundations product group.

As a Senior Technical Product Manager for Data Quality & Observability, you will be responsible for the end‑to‑end product strategy, delivery, and adoption of ’s enterprise data quality and data observability capabilities.

You will act as the product lead and subject matter expert for this domain, owning the vision for how data quality is defined, measured, monitored, and governed across the company. Working closely with data producers, analytics and ML practitioners, platform teams, and governance & risk stakeholders, you will ensure that ’s data ecosystem is trusted, reliable, explainable, and compliant with regulatory expectations.

This role is critical to enabling confident data‑driven decision‑making at scale, reducing operational and regulatory risk, and improving the overall reliability of ’s data and ML products.

As a Senior Technical Product Manager, you own the product vision, strategy, and adoption of ’s enterprise data quality and observability platform, enabling consistent, measurable, and actionable visibility into the health of data assets across their full lifecycle.

Your product(s) will provide capabilities such as:

• Defining and managing data quality expectations and checks across domains
• Monitoring freshness, completeness, accuracy, distribution, and volume of data assets
• Observing data pipelines, workflows, and downstream consumption to detect and diagnose issues
• Surfacing clear quality signals, SLAs, and trust indicators to both technical and business users
• Supporting auditability, traceability, and evidence required for regulatory and compliance use cases

The platform will serve multiple personas — from data engineers, analytics engineers, analysts, and ML practitioners, to data stewards, platform SREs, and governance, risk, and compliance stakeholders — each requiring different levels of insight, control, and assurance.

Poor data quality, limited observability, and fragmented ownership reduce trust in data, slow decision‑making, increase operational toil, and elevate regulatory risk. This role is focused on systematically addressing these challenges at enterprise scale, improving data reliability while reducing manual intervention and firefighting.

You will balance value creation for data & ML practitioners with the needs of control, risk, and regulatory functions, ensuring that data quality is not only measured, but actively managed and embedded into production workflows.

This horizontal role cuts across multiple platform products and domains, spanning OLTP and OLAP data sources, streaming and batch pipelines, analytical and AI assets (e.g. datasets, metrics, dashboards, features, models, and AI applications). It requires a deep understanding of how data is produced, transformed, and consumed across the enterprise.

As a senior member of the product craft, you will work closely with peer product leaders to define shared standards, drive alignment, and establish meaningful KPIs that measure improvements in data reliability, trust, and risk reduction at the platform and ecosystem level.

• User‑focused and outcome‑driven, keeping customer and business impact at the center of decision‑making
• Deep…