Backend Engineer, Monte Carlo
$160-190k
Plus equity
Data observability platform
Job no longer available
Data observability platform
201-500 employees
Job no longer available
$160-190k
Plus equity
201-500 employees
Company mission
To accelerate the world’s adoption of data by reducing data downtime.
Role
Who you are
- You have 4+ years of experience delivering production-grade backend code, performing code reviews, and working on cloud, data, and web applications
- You have strong Python skills (we use Django) or mastery of similar backend technologies in a large, complex codebase
- You test your work (with automation) and follow traffic as customers use your features
- You lead critical projects or initiatives within your team and organization
- You have experience in some of:
- Serverless applications, especially with AWS and Lambda
- Data-driven applications, with tools such as PySpark
- The needs of data engineers and analytics teams, such as with Snowflake, Databricks, Airflow, dbt, or many similar tools (our customers)
- Observability - a love of software APMs, debugging tools, and uptime metrics
- You collaborate with your team in a remote-first environment
- You get your urgency from user feedback and product vision
- You're pragmatic and biased towards action; you're able to see the bigger picture and reason about prioritization and scope
What the job involves
- We are looking for a Backend Engineer to take significant ownership in building Monte Carlo's cloud application for Data Observability
- The role will involve end-to-end development: helping formulate usability requirements and designs, full production implementation, and operations
- You will be collaborating with a small team of seasoned engineers, and your work will greatly impact our product and customers
- Building production-grade backend services and APIs to delight customers
- Owning major projects from inception to deployment, shipping at a rapid pace
- Architecting simple yet flexible solutions, and then scaling them as we grow
- Testing, releasing, and operating your code in production
- Navigating with some ambiguity while solving problems and pursuing solutions to difficult challenges
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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