Experience with scaling async systems, especially with gRPC, Kafka, Kubernetes
Proficiency in Go is a plus
Willingness to work in-person 5 days a week in San Francisco
Responsibilities
Build column encryption and analytics portal features
Streamline infrastructure by automating workloads
Enhance pipeline efficiency through technical tradeoffs
Develop native CDC connectors for unsupported data sources
Collaborate directly with customers to refine product offerings
Benefits
Healthcare coverage
401(k) plan
Unlimited paid time off (PTO)
Lunch and dinner provided
Visa sponsorship available
Full Job Description
About the Role
We are a small team based in San Francisco looking to hire an engineer that has a dedicated focus around distributed systems. As a founding engineer, you will have the opportunity to wear multiple hats, directly interact with our customers and play a crucial role in shaping the future of our product.
This is a challenging and dynamic role and you will be working at the forefront of data engineering, distributed systems and infrastructure.
What you should expect & examples of day-to-day tasks:
Building column encryption, launching our analytics portal and schema change alerts.
Building tooling to streamline and automate infrastructure workloads.
Introducing pipeline efficiencies by making tradeoffs between virtual memory and disk.
Building native change data capture (CDC) connectors to data sources that we do not yet support.
What we are looking for
Strong fundamentals in computer science
Pragmatic and care more about building the right thing vs. being right
Comfortable jumping around the stack and wearing different hats
Someone that wants to take an active role in defining the next gen data platform that utilizes stream processing and CDC to drive data latency to zero, while also focusing on ease-of-use and extensibility
Past experience working on scaling async systems and exposure to topics like gRPC, Kafka, Kubernetes, Helm is preferred but not required.
Proficiency writing in Go is preferred, but not necessary.
Tech stack
Frontend: TypeScript (React and Material UI)
Backend: Go, Postgres, Redis, Kafka and Elasticsearch
Infra: Terraform, Kubernetes, and Helm on GCP and AWS
