GTM Data Governance Manager; MDM

• Own the MDM roadmap and operating model for the account, contact, and organization hierarchy domains.
• Define golden record rules: matching, merging, survivorship, and parent/child hierarchies across CRM, billing, product, and support systems.
• Set data governance standards, including ownership, stewardship roles, definitions, and quality SLAs, in partnership with Sales, Marketing, Finance, and Customer Success.
• Run the processes for onboarding new data sources, handling change requests, and managing lifecycle events such as mergers, acquisitions, and customer reorganizations.
• Design and monitor data quality rules, scorecards, and dashboards covering completeness, accuracy, duplication, and timeliness.
• Drive remediation and report data health, risks, and progress to leadership with clear metrics and business impact.
• Specify integration patterns and acceptance criteria across Salesforce, the data warehouse, and enrichment providers.
• Work with Data Engineering and GTM Systems to build integration patterns and recommend build vs. buy for MDM, identity resolution, enrichment, and data quality tooling.
• Provide trusted, well-documented data products for analytics and AI use cases.
• Act as the data owner with Legal and Security on PII handling, GDPR and CCPA requirements, retention, and access controls.

• 8+ years of experience in data management, data governance, data engineering, or analytics, including 2+ years leading MDM or data quality programs.
• Hands-on experience designing match, merge, and survivorship rules and golden record or hierarchy models.
• Experience with Salesforce data models and CRM data quality at scale.
• Experience building and operating a data governance framework: policies, stewardship models, and SLAs.
• Ability to translate business needs into data requirements and explain technical tradeoffs to non-technical stakeholders.
• A track record of delivering cross-functional programs without direct authority.
• Experience at a B2B SaaS company with a product-led or hybrid sales motion (Nice to have).
• Familiarity with enrichment and firmographic data, entity matching approaches, and ML-assisted or LLM-assisted matching and cleansing (Nice to have).
• Working knowledge of data privacy regulations (GDPR, CCPA) and security frameworks such as SOC 2 (Nice to have).

Pay range: $129K - $210K

• Restricted Stock Units (RSUs)
• Health, vision, and dental insurance
• Mental health benefits

Launch Darkly allows teams to manage product features.