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GTM Data Governance Manager (MDM)

Pay
Multiple pay statements — pay source
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**
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.
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Work setting
Remote — work setting source
Listed location: Remote - US
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Employment
Not stated

Before you apply

Employer’s visa record
3 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.

What you’ll work on

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.

From the employer’s posting
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.
People management
Individual contributor stated — people management source
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

What you’ll bring

All qualifications

Core experience

  • 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.
Qualification wording
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.

About LaunchDarkly

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

Apply at LaunchDarkly

Posting record

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Status in our records
Live
First seen by us
Oct 22, 202622 days ago
Recorded sightings
27
Last seen by us
Nov 13, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

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.

Time since we first saw it

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.

LaunchDarkly is hiring

3 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Its jobs tend to stay up a long time
Hiring record

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Demand for Data Governance roles

New Data Governance postings at the employers we follow are up 170% over the last 6 weeks compared with the 6 before.

Weekly new Data Governance postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 74, the most 430, and the latest week had 428.
August 17Last week

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.

About the role

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.

Job description

View original posting ↗

About the Job:

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:

  • 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, and work with Data Engineering and GTM Systems to build them. 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.
  • Who You'll Work With: Data Engineering and GTM Systems build pipelines and Salesforce configuration. Legal and Security own privacy and security decisions, and you inform them as the data owner. You own the rules, standards, and acceptance criteria that tell everyone else what "correct" looks like.

Qualifications:

  • 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, with results you can describe.
  • 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.
  • 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.
    • Working knowledge of data privacy regulations (GDPR, CCPA) and security frameworks such as SOC 2.

Pay:

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 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.

*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.

About LaunchDarkly:

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:

  • Improving the velocity and stability of software releases, without the fear of end customer outages
  • Delivering targeted experiences by easily personalizing features to customer cohorts
  • Maximizing the business impact of every feature through the ability to experiment and optimize
  • Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types
  • Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability

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. 

Do you need a disability accommodation?

Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. 

Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @LaunchDarkly.com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly  directly for confirmed job openings and links to apply.

Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com.

Source details

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Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
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**
More source context
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.

Location & working pattern

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.
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

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