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Artie (YC S23) is hiring a founding engineer


Software that streams data from databases to warehouses in real-time

$150K – $200K / 0.50% – 1.00%


San Francisco, CA, US

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Robin Tang

About the role

We are a small team based in San Francisco looking to make our first hire.

Given that we’re small, you will have the opportunity to wear multiple hats. The work is dynamic and we are working at the forefront of distributed systems and data engineering. You will work directly with me (Robin) and have a critical role in shaping the future of our product.

You can expect the type of work to look something like this:

  • Spinning up a new data plane in a new AWS or GCP region with tools like Terraform and Helm
  • Working on optimizations for Artie Transfer, our open-sourced service product
  • Adding new functionality to our customer dashboard
  • Working with our customers on feature requests and answer any ambiguities

What we are looking for

  • Someone that wants to take an active role in defining the next generation data platform that utilizes streams processing and CDC to drive data latency to zero while spiking on ease-of-use and extensibility.
  • Strong fundamentals in computer science or related
  • Pragmatic and care more about building the right thing vs. being right
  • Comfortable jumping around the stack and wearing different hats
  • Past experience working on scaling asynchronous systems and exposure topics like: gRPC, Kafka and Kubernetes
  • Proficiency writing in Go is preferred, but not necessary.

Tech Stack

  • Go (Backend and Artie Transfer) and Kafka
  • Typescript
    • Marketing site uses Next.js and Tailwind
    • Customer dashboard uses React and Material UI
  • Infra: Terraform, Kubernetes and Helm
  • CI/CD: GHA and Concourse
  • Monitoring / alerting: Datadog, Pagerduty and Sentry

About Artie

We are building Artie, a real-time data streaming solution focused on databases and data warehouses. Typical ETL solutions leverage batched processes or schedulers (DAGs, Airflow), which cannot achieve real time data syncs. We leverage change data capture (CDC) and stream processing to perform data transfers in a more efficient way, which enables sub-minute latency.




Team Size:2

Location:San Francisco


Jacqueline Cheong

Robin Tang

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