Data Infrastructure Engineer

Description

TL;DR: Build the data infrastructure the the company agent runs on: ingestion, storage and query for millions of small tenants instead of one large one. You'll join the Data Platform team, and your work decides whether the apps people build on the company can rely on their data.

Why the company?

The company is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. The company is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on the company since its launch in November 2024. And we’re just getting started.

We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world.

The company is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software.

Responsibilities

• Build ingestion that accepts events from millions of the company apps, treats every producer as untrusted, and keeps one tenant's bad traffic from slowing or corrupting another's data.
• Build managed analytical storage for every user, including schema management, partitioning, and compaction of a constant stream of small writes.
• Make queries fast when you can't keep compute warm for every tenant.
• Build the runtime for agent-written connectors: isolated execution, credentials, scheduling, retries and state.
• Make cost per tenant measurable, then drive it down, through metering, limits and workload isolation.
• Expose data, metadata and tools to the the company agent so it can build software on customers' data.
• Run what you build, including observability, freshness and recovery.
• The tech stack
• We're building with tools that both humans and AI love:
• Languages: Go, Rust, Python, SQL
• Data: ClickHouse, BigQuery, Parquet on object storage
• Streaming & orchestration: Pub/Sub, Temporal
• Cloud: GCP, Cloudflare, AWS
• DevOps & tooling: GitHub Actions, Grafana, OTEL, Terraform
• And always on the lookout for what's next.
• About your application
• Please submit your application in English. It’s our company language, so you’ll be speaking lots of it if you join.
• We treat all candidates equally - if you’re interested, please apply through our careers portal.

Requirements

• An infrastructure engineer who has built and run data systems in production at scale, and wants the harder version of the problem: millions of tiny tenants on shared infrastructure.
• Deep experience in at least one layer (ingestion, storage formats and table layout, query execution, or orchestration), and the range to work across the others.
• Experience with multi-tenant or untrusted workloads: isolation, noisy neighbours, and keeping cost per tenant low.
• Good judgment on calls no one can check for you: the right abstraction, the tradeoff between cost and latency, whether a design holds at 10x.
• You work with AI agents end to end. Your output is the systems you build, not the code you type by hand.
• You ship, and you own what you ship in production.