Enterprise Customer Success Manager - West
Datadog · Denver, CO · Enterprise Customer Success
About this role
Datadog is hiring a mid-level Customer Success Manager in the sales function based in Denver, CO. The posting calls out experience with Datadog, Security, DevOps, Observability. Compensation is listed at $102,000–$110,000 per year.
- Role
- Customer Success Manager
- Function
- sales
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Denver, CO
- Department
- Enterprise Customer Success
More roles at Datadog
Job description
from Datadog careersAs an Enterprise Customer Success Manager, you will proactively drive new product attachment and effective strong relationships across our largest and most strategic customers. You’ll advocate for the customer internally and focus on a positive customer experience. Interactions are rooted in relationship-management, first and foremost, while also advocating for growth opportunities. Enterprise Customer Success Managers follow a well-defined methodology that helps them identify the customer's unique needs and clearly convey the value of the Datadog product.
At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.
What You’ll Do:
- Act as a strategic partner to customers, orchestrating cross-functional internal teams and engaging executive, technical, and business stakeholders to understand customer goals and translate them into a clear, deliverable Datadog value narrative.
- Proactively build and maintain executive relationships to deliver clear, outcome-driven value stories that connect Datadog technical use cases to measurable business results.
- Lead QBRs and strategic reviews as a forum to demonstrate impact, align on priorities, and define next-step initiatives.
- Analyze adoption and usage trends to quantify value delivered, extract insights from large datasets, identify gaps, and drive financially grounded commercial recommendations and strategic opportunities.