Sales Revenue Analyst - NYC
DatadogNew York, New York, USAPosted 7 April 2026
Job Description
The Team:
Datadog’s Revenue Operations Finance team continues to expand as we work continuously to improve and solve business problems.
The Sales Revenue team supports Datadog’s rapid growth by collaborating with teams across the organization, providing commercial, operational, and analytical support to ensure that Datadog's business and Sales organization continues to grow as rapidly and efficiently as possible.
In this role, you will gain hands-on experience managing commission processes at scale while collaborating cross-functionally with Finance, Sales, Strategy, and Operations. This is an excellent opportunity for anyone seeking high visibility, meaningful ownership, and a clear path for growth within a fast-paced SaaS environment.
We are looking for a Sales Revenue Analyst to join us in Boston, MA or New York, NY to support our team in managing global sales team compensation calculations and new business revenue recognition.
You Will:
Own the monthly sales commission process across multiple sales segments, ensuring accuracy, timeliness, and operational excellence.
Improve day-to-day operations by identifying process gaps, fixing inefficiencies, and building practical tracking for new initiatives as the business grows.
Analyze compensation results to identify trends, surface risks, and provide actionable insights to leadership
Review deal structures and financial terms to ensure alignment with compensation policies and revenue recognition requirements
Partner cross-functionally with Finance, Sales, Systems and Strategy to support compensation plan execution and business initiatives
Maintain and optimize compensation systems, reporting and dashboarding by leveraging tools such as Salesforce and CaptivateIQ to elevate sales performance visibility, improve data integrity, and enhance the overall experience for sales teams and cross-functional stakeholders
Partner closely with Datadog’s most senior leaders to evaluate, design, and operationalize new sales strategy programs
You Are:
Job Specific:
2-3 years of experience in Finance, Sales Operations, Revenue Operations, Incentive Compensation, or Business Analytics
Highly analytical with advanced Excel skills and experience working with large datasets
A strong problem solver who can recognize patterns and translate data into insights
Comfortable operating in a fast-paced, high-growth environment with shifting priorities
Soft Skills:
Demonstrated experience thinking strategically about complex issues
Excellent interpersonal skills with experience presenting to teams of various functions and levels
Project ownership and delivery - work closely with cross-functional teams to manage stakeholders and coordinate, plan and prioritize tasks
Bonus Points:
Experience with SaaS company economics, deal structuring, and monthly recurring revenue business model
Experience working with compensation business automation tools (such as CaptivateIQ)
Experience in a high-growth
SaaS company and/or multi-national public company
Familiarity with Tableau, Metabase, and (or) other business intelligence systems
Experience in sales-facing role or working with C-suite executives
About Us:
Datadog is the monitoring and security platform for cloud applications. Our SaaS product is used by organizations of all sizes across a wide range of industries to enable digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stack, allowing for seamless collaboration and problem-solving among Dev, Ops and Security teams globally. Given the resilience of cloud technologies and importance placed today in digital operations and agility, Datadog continues to innovate and is well positioned for the long term.
#LI-Hybrid
Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offe ... (truncated, view full listing at source)
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