Senior Software Engineer
San Francisco, CAFull-time$150–250K/yrPosted 2mo agoStill listed 3 days ago
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Job overview
Artie is hiring a Senior Software Engineer. Artie is a real-time streaming platform that moves production data across systems with zero maintenance, enabling high‑volume data replication for engineering teams. The Senior Software Engineer will join a small San Francisco team as a founding engineer, focusing on distributed systems, building tooling, and shaping the next‑gen data platform.
Key focus areas include Build column encryption, launch analytics portal and schema change alerts, Build tooling to streamline and automate infrastructure workloads, and Introduce pipeline efficiencies by balancing virtual memory and disk.
Successful candidates bring 3+ Years Experience and Work In-Person In San Francisco. Important skills include Distributed Systems, Computer Science Fundamentals, Pragmatism, Full Stack Development, Stream Processing, and Change Data Capture. Preferred (not required): Scaling Async Systems, gRPC, Kafka, and Kubernetes.
Skills & qualifications
Skills
Qualifications
Full job description
Artie Software that streams data from databases to warehouses in real-time
Senior Software Engineer $150K - $250K • San Francisco, CA, US Job type Full-time Role Engineering, Backend Experience 3+ years Visa Will sponsor Connect directly with founders of the best YC-funded startups. Apply to role › Robin Tang Founder Robin Tang Founder About the role About us Artie is a real-time streaming platform that moves production data across systems in real time, with zero maintenance. We make high-volume data replication simple, reliable, and scalable for engineering teams.
Our platform powers mission-critical use cases including fraud and risk monitoring, inventory visibility, customer-facing analytics, and AI workloads. Artie is built for engineers who care about performance, reliability, and operational simplicity — and we’re growing fast.
We’re trusted by teams like ClickUp, Substack, and Alloy, and backed by top-tier investors including Y Combinator, General Catalyst, Pathlight Ventures, and the founders of Dropbox and Mode.
About the Role We are a small team based in San Francisco looking to hire a founding 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.
- Happy to work in-person 5 days/week in San Francisco’s Financial District with the rest of the team. Tech stack
- Frontend: TypeScript (React and Material UI)
- Backend: Go, Postgres, Redis, Kafka and Elasticsearch
- Infra: Terraform, Kubernetes, and Helm on GCP and AWS 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.
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