Director, Data Governance

Whoop•Boston, MA

19h•$190,000 - $230,000•Onsite

About The Position

WHOOP is seeking a Director, Data Governance to establish and lead Data Governance as a new function within the Data, Analytics & AI (DAA) organization. This role reports to the VP of Data, Analytics and AI and is responsible for defining the strategy, operating model, and roadmap for data ownership, contracts, event taxonomy, cataloging, access policy, data quality standards, and privacy and compliance. The Director will lead through influence, clear standards, and strong cross-functional partnerships, building the governance layer on top of WHOOP's mature data platform. This includes formal ownership models, data contracts, an event taxonomy, cataloging and discovery, classification frameworks, and policies for scaling into regulated environments. The role involves building and leading a team, championing AI-powered approaches for data health monitoring, and collaborating with various technical and business teams to ensure trusted data is a shared responsibility.

Requirements

10+ years in data, engineering, or data governance roles, with a strong background in data governance, data quality, data engineering, or data platform, and at least 4 years leading and building teams.
Direct experience building data governance programs or frameworks, ideally in a high-growth environment where governance was not yet formalized.
Deep hands-on experience with modern data stack tooling: Snowflake, dbt, Airflow/orchestration, and data catalog/lineage tools.
Working knowledge of healthcare data regulations (HIPAA), or willingness to develop deep expertise quickly given the WHOOP expansion into regulated healthcare products.
Experience implementing data quality frameworks with automated monitoring and alerting.
Experience with access control design and administration in cloud data platforms (Snowflake RBAC, row-level security, dynamic data masking).
Demonstrated ability to drive cross-functional alignment on data standards and policies, and to lead highly cross-functional initiatives. Comfortable influencing engineering, product, and business teams.
Experience operating in regulated environments.
Proven track record managing data oversight for complex research initiatives, such as IRB-regulated studies or trials or regulatory filings for the FDA.
Excellent executive communication and organizational leadership. Able to translate technical governance concepts into business value for non-technical stakeholders and senior leadership.
A player-coach orientation. Willing to be deeply hands-on while building repeatable processes and growing a team.
Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.

Responsibilities

Define and lead the data governance strategy, operating model, and roadmap spanning data ownership, contracts, event taxonomy, cataloging, access policy, data quality standards, and privacy and compliance (HIPAA, GDPR, CCPA), aligned with the DAA strategy.
Build, lead, and coach a small, senior team, developing your people while partnering closely with Staff level technical leaders across the org.
Establish a formal data ownership model, partnering with engineering and business stakeholders to assign stewardship and accountability for critical datasets.
Define the standards for data contracts between producing and consuming teams, covering schema stability, SLA adherence, and breaking-change management, with implementation owned by Data Platform & Engineering.
Own the event taxonomy governance framework, bringing structure to event tracking and standardizing how product and engineering teams define, name, and instrument events across platforms.
Set data quality standards (freshness, validation, monitoring) and the incident response expectations, partnering with Platform to operationalize automated testing and anomaly detection.
Champion AI powered governance approaches that proactively surface quality issues, ownership gaps, policy violations, and compliance risks.
Partner with GRC, Legal, and InfoSec to define the privacy, HIPAA, and compliance standards for how sensitive data is handled, which the platform then implements.
Define role-based access policy across the data platform, balancing security with self-service accessibility, with enforcement engineered by Platform.
Embed governance standards directly into engineering and developer workflows so the right way is the easy way, rather than relying on manual processes.
Develop governance metrics and reporting to track adoption, compliance, and data health across the organization.
Build a culture where trusted data is a shared responsibility across technical and business functions.