About the role
DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities. Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos.
The role You'll join a small, high-impact Customer Success team responsible for driving adoption and long-term value across a portfolio of enterprise accounts. Your job is to make sure customers don't just get DataHub up and running — they actually use it, love it, and expand it across their organization. You'll guide customers through onboarding, help them get unstuck, and build relationships that turn early deployments into lasting programs. You'll work with data teams on practical setup questions one day, and walk an executive through their adoption progress the next.
What you'll do Own a portfolio of enterprise accounts end-to-end, from onboarding through renewal and expansion Partner with customers to build adoption plans grounded in their specific goals and data maturity Help customers through initial setup, configuration questions, and common troubleshooting scenarios Translate adoption progress and business value into clear narratives for executive stakeholders Identify at-risk accounts early, understand the root cause, and get things back on track Collaborate with Product and Engineering to share customer feedback and influence the roadmap Build repeatable playbooks and resources that help the CS team scale What you'll bring Required Familiarity with data governance, data cataloging, or metadata management more broadly Exposure to common data stack tools like dbt, Airflow, Snowflake, or Databricks — you don't need to be an expert, but you know what they do Three or more years in a client-facing role managing multiple accounts at once (Customer Success, Account Management, Technical Account Management, or similar) Comfortable communicating with both data practitioners and business stakeholders — you can adjust your message depending on the room Strong written and verbal communication skills — you write clearly, prepare thoroughly, and run meetings that end with decisions
