Director, Data Governance

Whoop•Boston, MA

3d•$190,000 - $230,000•Onsite

About The Position

WHOOP is seeking a Director, Data Governance to establish and lead Data Governance as a new pillar within its Data, Analytics & AI (DAA) organization. Reporting to the VP of Data, Analytics and AI, this is the first dedicated leader of the function and will define its strategy, operating model, and roadmap for data ownership, contracts, event taxonomy, cataloging, access policy, data quality, privacy, and compliance. Governance will set the policies and standards, while the Data Platform & Engineering pillar will engineer and implement them. The role therefore depends on influence, clear standards, and cross-functional partnership. WHOOP has a mature data platform; this role will build the governance layer on top of it, including formal ownership models, data contracts, event taxonomy, cataloging and discovery, classification frameworks, and policies that support growth into regulated environments. The Director will build and lead a team and champion AI-powered approaches to continuously monitor data health and trust. The role combines strategic leadership with hands-on work, from presenting frameworks to senior leaders to developing standards with engineers. It partners across Data Platform & Engineering, Analytics, Data Science, Product, GRC, Legal, InfoSec, and RAD to earn trust, drive adoption, and deliver enforceable governance outcomes. The role is based in WHOOP’s Boston, Massachusetts office. The successful candidate must be prepared to relocate if necessary to work from that office. WHOOP describes total compensation as base salary, equity, and benefits. The U.S. base salary range for this full-time role is $190,000–$230,000; the successful candidate will also receive benefits and an equity package.

Requirements

At least 10 years of experience in data, engineering, or data governance roles, with a strong background in data governance, data quality, data engineering, or data platforms.
At least 4 years of experience leading and building teams.
Direct experience building data governance programs or frameworks.
Deep hands-on experience with modern data stack tools, including Snowflake, dbt, Airflow or other orchestration, and data catalog or lineage tools.
Experience implementing data quality frameworks with automated monitoring and alerting.
Experience designing and administering access controls in cloud data platforms, including Snowflake RBAC, row-level security, and dynamic data masking.
Demonstrated ability to align cross-functional teams on data standards and policies and lead initiatives involving 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, including the ability to explain technical governance concepts as business value to non-technical stakeholders and senior leaders.
Player-coach orientation, with willingness to be hands-on while building repeatable processes and growing a team.
Strong commitment to embracing and leveraging AI tools in day-to-day work and ensuring AI-assisted work meets the same high-quality standards as personal contributions.
Must be prepared to relocate if necessary to work out of WHOOP’s Boston, Massachusetts office.

Nice To Haves

Experience building governance in a high-growth environment where governance was not yet formalized.
Working knowledge of HIPAA, or willingness to develop deep expertise quickly as WHOOP expands into regulated healthcare products.

Responsibilities

Define and lead the data governance strategy, operating model, and roadmap for data ownership, contracts, event taxonomy, cataloging, access policy, data quality standards, privacy, and compliance, aligned with DAA strategy.
Build, lead, and coach a small, senior team, developing team members and partnering with Staff-level technical leaders.
Establish a formal data ownership model and partner with engineering and business stakeholders to assign stewardship and accountability for critical datasets.
Define standards for data contracts between producing and consuming teams, including schema stability, SLA adherence, and breaking-change management; Data Platform & Engineering owns implementation.
Own the event taxonomy governance framework and standardize how product and engineering teams define, name, and instrument events across platforms.
Set data quality standards for freshness, validation, monitoring, and incident response, partnering with Platform to operationalize automated testing and anomaly detection.
Champion AI-powered governance approaches to surface quality issues, ownership gaps, policy violations, and compliance risks proactively.
Partner with GRC, Legal, and InfoSec to define privacy, HIPAA, and compliance standards for handling sensitive data for implementation by the platform.
Define role-based access policy across the data platform, balancing security with self-service accessibility; Platform engineers enforcement.
Embed governance standards in engineering and developer workflows so compliant practices are easy to follow and do not rely on manual processes.
Develop governance metrics and reporting to track adoption, compliance, and data health across the organization.
Build a culture in which trusted data is a shared responsibility across technical and business functions.