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Revenue Operations Manager; Deal Desk

Job in Denver, Denver County, Colorado, 80285, USA
Listing for: Crusoe Energy Systems
Full Time position
Listed on 2026-10-11
Job specializations:
  • Business
    Financial Analyst, Business Analyst, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 110000 - 170000 USD Yearly USD 110000.00 170000.00 YEAR
Job Description & How to Apply Below
Position: Revenue Operations Manager (Deal Desk)
  • We’re looking for a Revenue Operations Manager to own our deal desk function and lead the implementation, management, and ongoing optimization of our CPQ. This role sits at the intersection of pricing strategy, sales enablement, and systems ownership
  • You’ll be the Revenue Operations partner for Account Executives navigating complex, technical deals, while also building the infrastructure that lets the sales org quote and close faster
  • Advise AEs on deal structuring, negotiation tactics, and creative packaging to protect margin while removing friction to close. Serve as the primary point of contact for AEs on non-standard deals, terms, pricing, and discounting
  • Set and continuously adjust pricing in response to a dynamic market, translating fast-moving conditions into clear, real-time pricing guidance for the GTM , product, and Finance teams
  • Conduct ongoing market rate analysis leveraging any competitor pricing intelligence, internal win/loss data, and segment-level price sensitivity to recalibrate price points, discounts, and approval thresholds
  • Own the deal approval workflow, ensuring the deals get the right level of scrutiny without becoming a bottleneck. Partner with Sales Leadership, Finance, and Legal on exception approvals, non-standard terms, and contract structuring
  • Track deal desk metrics: discount trends, approval cycle time, win rates by deal type, price realization. Build dashboards and reporting to give leadership visibility into pricing trends and deal desk throughput
  • Own end-to-end implementation, configuration, and maintenance of the CPQ system
  • Build and maintain product bundles, pricing rules, discount schedules, approval matrices, and quote templates. Continuously audit CPQ data integrity (product catalog, price books, rules logic) to ensure quotes reflect our latest pricing strategy
  • Partner with Sales, Finance, and Product on new product launches, packaging changes, and price book updates, translating them into CPQ configuration
  • Identify and eliminate friction in the quote-to-cash process. Reduce quote turnaround time and manual workarounds
  • Train, enable, and support AEs and sales managers on CPQ best practices
Benefits
  • Health & wellbeing:
    Comprehensive health benefits designed to support your overall wellness
  • Time away:
    Paid time off for vacations, family bonding, and unexpected needs
  • 401(k) match:
    Build your financial future with our 401(k) matching program
  • Mental wellness:
    Resources and support for your emotional wellbeing and navigating life’s challenges

We’re specifically looking for someone who has experience setting defensible prices with novel deal structures with limited comps in a dynamic market. Our is a technical, consultative sale, where deal complexity, competitive dynamics, dynamic pricing make “one price fits all” impossible

Experience at a growth-stage company where you’ve had to build or rebuild processes from scratch

Hands-on CPQ implementation and administration experience (Salesforce CPQ, Deal Hub, Panda Doc, Zuora, or similar)4-7 years of experience in Revenue Operations focusing on running a deal desk function, advising AEs on deal structuring, pricing strategy, and contract negotiations, preferably within a high growth, B2B technology environment

Strong Excel/Sheets modeling skills for pricing analysis; SQL or reporting tool experience a plus Proven track record setting and adjusting prices in a dynamic, fast-moving market. Strong understanding of market rate benchmarking and competitive pricing analysis. Experience pricing usage-based and consumption-based products

Experience with hyperscalers, GPU clouds, or high-performance compute environments

Familiarity with large-scale AI training and inference architectures

Track record of working with Fortune 500 enterprises and digitally native businesses on transformative infrastructure deals

Strong network in the AI/ML and enterprise technology ecosystem

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