About Tarsal
Tarsal is data infrastructure for security teams. As security data grows 25% year over year, security teams desperately need access to best-in-class data infrastructure. Tarsal bridges the gap between the modern data stack and security teams, pioneering the modern security data stack.
Tarsal launched early 2023 and met with immediate product-market fit; we've grown to land multiple enterprise customers without a sales team. Our engineering challenges now revolve around servicing our customer demand so we can continue winning the market.
Cofounded by serial cybersecurity founder Barrett Lyon (previously exited at $370M), along with senior engineers Sunny Rekhi and Manmitha Gundampalli, Tarsal has raised over $6M from Y Combinator, Abstract Ventures, Harpoon Ventures, and Mango Capital, among many other supportive investors.
About the role
Skills: Go, Python, DockerYou'll wear many hats, so this is a generalist role -- we'll need someone who is strong in backend and infrastructure engineering but is willing to tackle unfamiliar technologies.
What You’ll be Doing
- Improve latency of our end to end data processing by optimizing reads from source systems, writes to destination systems, and pipeline throughput
- Building toward our expansive 2024 feature roadmap informed by our current and prospective enterprise customers
- Build integrations to a suite of security, SaaS, and identity applications
- Support our customers via Slack + triaging their feature requests
Requirements:
- Expertise in Golang, Python, and AWS
- 3+ years of experience
Pluses (but not required):
- Experience working on high scale data pipelines
- Experience working with cloud data warehouses like Snowflake
- Experience with Docker
Technology
Tarsal is a petabyte scale data pipeline. Our stack is Golang, Python, and React. Hosted on AWS.
Interview Process
Before anything else, please take a look at our culture doc to see if we're a good fit: https://tarsal.notion.site/Tarsal-s-Culture-1d0327a016da4b60a40aca8dbf1d4070
First, you'll do a ~15m phone call or Zoom with our cofounder/CEO. We'll touch briefly on your experience, expectations, and determine whether we're a potential fit.
Then, we'll do a standard, Leetcode-esque algorithm coding interview. This will be 45 minutes.
If that goes well, we'll do a "virtual" onsite of two sessions back to back. One will be a 45m system design interview where we give you constraints and ask you to design a system, and then we'll change the constraints and work with you on how the system design should change. This will be an exercise to see how you think, but also how we work together. After that, we'll do a 45m session on you: things you've worked on, mistakes you've made, etc.
Our last step is to do a few reference checks, after which we'll extend a full time offer. We can move as fast as you need.
