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Acceldata

Data observability platform improving data reliability

VP of Enterprise Sales

Account ExecutiveConfirmed live in the last 24 hours
Full-timeCampbell, CA, USANo salary listed

About the Job

Requirements

  • At least 5 years as a first-line sales leader managing enterprise account executive teams at Series B–D startups selling into Fortune 500 companies.
  • Proven ability to build and scale teams from 4–6 to 10 or more representatives, including direct recruiting of enterprise sellers.
  • Experience managing teams that use MEDDPICC and Challenger/JOLT as operating systems, including creating inspection cadences, coaching representatives in the methodologies, and holding teams accountable.
  • Demonstrated ability to manage team-level forecast accuracy and pipeline governance, with a history of forecasting within a tight variance.
  • At least 7 years of quota-carrying enterprise software sales experience before moving into leadership, with a record of exceeding new ARR quotas in Fortune 500 or Global 2000 accounts.
  • Deep expertise in data management, including data quality, governance, observability, orchestration, catalog, reliability, or adjacent categories.
  • Ability to communicate substantively with data engineers and Chief Data Officers.
  • Technical acumen spanning open-source technologies and Hadoop, enterprise data management, cloud service providers, containers and Kubernetes, ETL, databases and data warehouses, and the modern data stack.
  • Experience with complex, multi-stakeholder sales cycles involving six- to seven-figure ACV and sales cycles of 6–12 months or longer.
  • Ability to operate amid ambiguity and create a playbook where one does not exist.
  • Ability to work hands-on in deals, run demonstrations, or prospect alongside representatives when needed.
  • Fluency with Salesforce, LinkedIn Sales Navigator, Outreach, Gong, Perplexity, Dripify, AI-driven sales tools, and Storylane.
  • Willingness to travel up to 50% for customer meetings, team onsites, trade shows, and enterprise events.
  • Must be based in the United States and able to work effectively in a distributed team environment with high accountability and communication.

Responsibilities

  • Lead, coach, and develop the current team of four enterprise account executives, scaling the team to 8–10 by year-end through recruiting.
  • Establish a MEDDPICC-driven inspection cadence with deal reviews, pipeline reviews, and forecast calls, ensuring representatives work rigorously and accountably.
  • Coach representatives using Challenger and JOLT principles, conduct deal review sessions using Gong, diagnose stalled deals at the champion and economic-buyer levels, and develop representatives’ ability to teach, tailor, and take control.
  • Own recruiting, onboarding, ramping, performance management, and talent upgrades as needed; attract and retain top enterprise sellers.
  • Drive representative productivity metrics, including ramp time, quota attainment distribution, pipeline creation per representative, and activity-to-outcome ratios.
  • Own the North American new-logo ARR target and team attainment across deal sizes and product lines.
  • Define and enforce pipeline coverage discipline and MEDDPICC-aligned stage-gate criteria, set coverage-ratio expectations, and ensure pipeline reaches 3–4 times commit.
  • Run a forecast methodology that distinguishes Commit, Most Likely, and Upside, and deliver accurate forecasts.
  • Engage directly in strategic and complex opportunities, helping account executives navigate enterprise procurement, legal negotiations, and C-suite engagement.
  • Monitor and improve win rates, average selling price, and sales-cycle times.
  • Translate product capabilities into differentiated value propositions for enterprise buyers, including Chief Data Officers, VPs of Data Engineering, and technical stakeholders.
  • Use Challenger-based rational drowning to create urgency around business pain in data quality, reliability, and governance.
  • Maintain competitive intelligence across data observability, data quality, and data management to inform positioning and deal strategy.
  • Partner with Product to communicate enterprise customer requirements, roadmap priorities, and competitive gaps for product development.
  • Collaborate with Marketing on account-based programs, ideal customer profile refinement, event strategy, and pipeline-generating content.
  • Ensure clean handoffs to Customer Success, protect expansion revenue, and establish long-term account health from the start of the sales cycle.
  • Represent the sales function at the leadership table and contribute to company strategy, pricing decisions, and go-to-market evolution.
  • Within the first 90 days, assess team performance, pipeline health, and territory coverage; establish MEDDPICC inspection cadence and forecast rhythm; identify hiring priorities and begin recruiting; and build cross-functional relationships with Product, Marketing, and Customer Success.
  • Within six months, scale the team to 6–8 account executives with new hires ramping against onboarding milestones; achieve pipeline coverage of 3–4 times commit with stage-gate adherence; deliver credible forecasts within acceptable variance; and measurably improve win rates, average selling price, or cycle time against baseline.
  • Within 12 months, build the team to 8–10 or more contributing account executives, meet or exceed the team ARR target, demonstrate readiness for a second-line structure through team depth and operating maturity, and articulate a strategic territory and team plan for the following year.

About the Company

Acceldata

Data observability platform improving data reliability

Acceldata provides a data observability platform for data teams to improve data reliability, monitor data health, and optimize large data infrastructures while reducing costs. It uses machine learning-driven automation to detect issues, perform data quality checks, and deliver actionable insights, integrating with existing data stacks through features like Spend Intelligence, Data Reliability, and Operational Intelligence. The platform differentiates itself by combining data quality, reliability, and cost optimization in one solution for sizable data environments and transitions to open-source technologies, not just monitoring. Its goal is to help organizations maximize the value of their data investments by making data reliable, affordable, and ready for decision-making.

Company size
201-500
Company stage
Series C
Total funding
$105.6M
Headquarters
Campbell, CA
Founded
2018

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