Pay
$105K–$170K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 113 postings in the last year. Stated ranges, not salaries paid.
Remote - US
Live, first seen by us 22 days agoTarget pay ranges based on Geographic Zones* for Level 4: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $152,900 - $210,210** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200**
Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $152,900 - $210,210** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200** Zone 3: All other US locations - $129,900 - $178,640**
Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200** Zone 3: All other US locations - $129,900 - $178,640** LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location.Read the full posting
Listed location: Remote - USRead the full posting
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.
Design and monitor data quality rules, scorecards, and dashboards covering completeness, accuracy, duplication, and timeliness.
Responsibilities: 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.
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.
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, and work with Data Engineering and GTM Systems to build them. Recommend build vs. buy for MDM, identity resolution, enrichment, and data quality tooling.
AI-powered workflows are only as good as the customer data underneath them. LaunchDarkly helps engineering teams ship software faster and more safely through feature management, experimentation, and AI delivery tooling. As our GTM Data Governance Manager (MDM), you will set the rules that make our core customer data (accounts, contacts, subscriptions, and users) accurate, consistent, and trusted across Salesforce, our billing and finance systems, marketing automation, product usage data, and the data warehouse. This is an individual contributor role with real ownership of the data model and its standards. You will partner with Data Engineering, GTM Systems, Finance Systems, Legal, and Security to put those standards into production. Your work is the foundation for reliable reporting, accurate territory and segmentation, clean pipeline attribution, and the AI workflows that depend on high-quality data. Responsibilities:Read the full posting
8+ years of experience in data management, data governance, data engineering, or analytics, including 2+ years leading MDM or data quality programs.
Experience at a B2B SaaS company with a product-led or hybrid sales motion, including mapping product users and workspaces to CRM accounts.
Hands-on experience designing match, merge, and survivorship rules and golden record or hierarchy models, with results you can describe.
Familiarity with enrichment and firmographic data, entity matching approaches, and ML-assisted or LLM-assisted matching and cleansing.
Experience with Salesforce data models and CRM data quality at scale.
Experience building and operating a data governance framework: policies, stewardship models, and SLAs.
Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise.
In the employer’s words · Read in context
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$105K–$170K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 113 postings in the last year. Stated ranges, not salaries paid.
Day 22
Similar jobs usually come down between day 6 and day 52.
From 1,782 similar postings that came down. Coming down is not always a hire.
3 open jobs
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New Data Governance postings at the employers we follow are up 170% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Governance, by the work the posting describes.
Data governance staff keep a company's data accurate, documented and used within the rules. They agree what key fields mean, set up quality checks, track who owns each dataset and look after master data.
Postings ask for SQL, a governance tool such as Collibra or Informatica, knowledge of privacy and data rules, and a lot of work with other teams.
A data engineer builds the systems that move data; governance staff set and check the standards that data has to meet.
AI-powered workflows are only as good as the customer data underneath them. LaunchDarkly helps engineering teams ship software faster and more safely through feature management, experimentation, and AI delivery tooling. As our GTM Data Governance Manager (MDM), you will set the rules that make our core customer data (accounts, contacts, subscriptions, and users) accurate, consistent, and trusted across Salesforce, our billing and finance systems, marketing automation, product usage data, and the data warehouse.
This is an individual contributor role with real ownership of the data model and its standards. You will partner with Data Engineering, GTM Systems, Finance Systems, Legal, and Security to put those standards into production. Your work is the foundation for reliable reporting, accurate territory and segmentation, clean pipeline attribution, and the AI workflows that depend on high-quality data.
Pay:
Target pay ranges based on Geographic Zones* for Level 4:
LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location.
*Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas.
**Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary.
Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations.
The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by:
At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com.
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Selected passages from the saved posting. Check the full description for conditions and exceptions.
Target pay ranges based on Geographic Zones* for Level 4: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $152,900 - $210,210** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200**
Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $152,900 - $210,210** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200** Zone 3: All other US locations - $129,900 - $178,640**
More relevant text appears in the full description.
Remote - US
- Nice to Have - Experience at a B2B SaaS company with a product-led or hybrid sales motion, including mapping product users and workspaces to CRM accounts. - Familiarity with enrichment and firmographic data, entity matching approaches, and ML-assisted or LLM-assisted matching and cleansing.
No clear work-authorization passage found. Eligibility is unconfirmed.