Senior Cloud Performance Engineer United Kingdom; remote

Recognized on the 2025 Forbes Cloud 100 list, Click House is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, Click House leads the market in real-time analytics, data warehousing, observability, and AI workloads.

The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.

We’re on a mission to transform how companies use data. Come be a part of our journey!

The Cloud Engineering team is responsible for building the cloud‑native Click House Cloud Platform that will transform the OLAP space. Our team is looking for exceptional performance engineers with a proven track record of understanding the performance limits of different distributed databases and creating tools for measuring the performance and scalability of complex systems. The ideal candidate for this position is a distributed systems performance engineer with a strong background in database benchmarking, test automation, system engineering, performance analysis, and capacity management.

This role is a unique opportunity to make a significant impact on our elastic, limitless scale, high‑performance, serverless Click House Cloud.

• Benchmark system performance, database performance analysis, capacity sizing and optimization.
• Troubleshoot and debug applications, server errors, logs, and triage accordingly.
• Recommend configuration tuning/optimizations for performance bottlenecks.
• Work closely and partner with Click House's core development team, cloud team, and security team to improve the performance of Click House Cloud.
• Plan, enable, and drive Chaos initiatives across Engineering teams, based upon internal priorities.
• Develop, deploy and manage tools to systematically run chaos experiments and measure impact.
• Enjoy working on, and gaining a deep understanding of, large‑scale distributed systems.
• Study the problems in the software resilience, operational, and delivery spaces.
• Extend our entire backend to enable Chaos Engineering techniques in the system.
• Observe running systems, and determine/prioritize innovative ways to disrupt them.

• You have 6+ years of relevant software development industry experience building and operating scalable, fault‑tolerant, distributed systems.
• Software development experience in Go, C/C++, Java, or similar.
• Experience with concurrency, multithreading, and the deployment of distributed system architectures.
• Experience developing cloud infrastructure services, preferably with Kubernetes.
• Experience leading and shipping large‑scope technical projects in collaboration with multiple experienced engineers.
• Expertise with a public cloud provider (AWS, GCP, Azure) and their infrastructure as a service offering (e.g. EC2).
• You have excellent communication skills and the ability to work well within a team and across engineering teams.
• You are a strong problem solver and have solid production debugging skills.
• You are passionate about efficiency, availability, scalability and data governance.
• You thrive in a fast‑paced environment, and see yourself as a partner with the business with the shared goal of moving the business forward.
• You have a high level of responsibility, ownership, and accountability.

For roles based in the United States, the typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.

These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.

An individual’s placement within the range will depend on…