Enterprise Sales Development Representative, Monte Carlo
More information about location
Data observability platform
Open for applications
Data observability platform
201-500 employees
Open for applications
More information about location
201-500 employees
Company mission
To accelerate the world’s adoption of data by reducing data downtime.
Role
Who you are
- 1+ years work experience in either a pipeline generation role or a heavy process orientation role
- Demonstrated track record in an early-stage company or highly ambiguous environment
- Experience with a complex and consultative sales
- Ownership: Intrinsically motivated to build something special, with a high degree of accountability and bias for action. We don’t have a lot of answers - go find them
- Prioritization: Ability to organize and structure a process and maintain focused discipline on the most important things
- Integrity: Worthy of trust, honest about failures, acts in a way that makes us proud of the journey
- Customer orientation: Deep empathy for our customers with a focus on adding value and happiness
- Beat the odds: Set crazy goals — hold self to a high standard to overachieve them. Fail forward: Be comfortable making mistakes, always own them and help the company learn from them
- Speed: Sense of urgency to get results and learnings as quickly as possible
What the job involves
- We’re looking for an Enterprise Sales Development Rep (SDR) who will be responsible for driving new enterprise pipeline for Monte Carlo
- His role will focus on outbound prospecting, identifying, engaging, and booking meetings with key decision makers amongst their book of business
- Partnering closely with an Account Executive, you’ll develop and execute creative outreach strategies to educate the market on Monte Carlo and generate qualified opportunities
- This individual will also triage inbound leads based on our ICP definition and follow up in a timely manner to convert them into qualified opportunities for our sales team
- Additionally, you’ll help build and refine the enterprise outbound playbook, collaborating with marketing to test messaging, share feedback from the field, and achieve joint pipeline goals
Salary benchmarks
Our take
Dozens of billion dollar companies have emerged with a shared focus on easing the burden on engineering teams constantly battling to guarantee reliability in their products. For example, New Relic revolutionized application observability. In the same way, Monte Carlo is tackling data observability.
The service pulls information from metadata log metrics to help teams understand their data health, and if something breaks the product will send proactive notifications. The product is an off-the-shelf SaaS offering that customers can integrate and customize over time.
The company has won some major clients including big tech companies like Affirm and Intuit, but also JetBlue, PepsiCo, CNN, The New York Times, Asics, Rivian and others from many sectors. Its goal is to help companies reduce data downtime and the time data engineers must spend on tedious data quality tasks.
'Data Observability’ became a point of furore in venture capital in 2022. For example, in the span of one week, just three companies raised more than $400 million between them. Staying at the forefront of this industry is an interesting challenge for Monte Carlo, and it met it in 2024 with product enhancements that include new GenAI capabilities for its platform.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
32% employee growth in 12 months
Company
Funding (last 2 of 4 rounds)
May 2022
$135m
SERIES D
Aug 2021
$60m
SERIES C
Total funding: $236m
Company HQ
Dolores Heights, San Francisco, CA
Leadership
Barr Moses
(CEO)Previously VP of Customer Success Operations for Gainsight. Originally trained as a Management Consultant with Bain & Company. Also attended Stanford where they studied Mathematics and Computer Science.
Lior Gavish
(CTO)Previously SVP of Engineering for another tech startup, Barracuda. Also previously worked for PayPal and holds an MBA from Stanford University.
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