Cloud Engineer - Product Metrics
ClickHouseUnited States (remote)Posted 9 March 2026
Job Description
About ClickHouse
Recognized on the 2025 Forbes Cloud 100 list, ClickHouse 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, ClickHouse 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!
About the team
The Product Metrics team owns the collection, storage, and serving of metrics collected from customers' ClickHouse instances. As a part of the team you will be responsible for designing, building, operating and maintaining components of the petabyte-scale platform that stores trillions of records and processes millions of new events every second, owning its reliability, performance and availability. Our stack is built using Golang, runs in Kubernetes, and is, of course, stored in ClickHouse. The team’s responsibilities include gathering and processing data for the internal billing and accounting system as well as customer-facing dashboards that provide our customers with immediate insights and analytics. The Product Metrics system is specifically designed to prioritize delivery guarantees, precision, and accuracy in handling extensive data volumes. Its primary goal is to provide data that is both prompt and accurate, supporting reliable operational decisions and enhancing the overall customer experience.
What will you do?
Take an active part in determining the roadmap for the Product Metrics team
Work closely within the team to deliver new features, iterate and improve them
Design, build, operate, and maintain business-critical petabyte-scale systems
Be responsible for the performance, reliability, availability and cost-efficiency of the Product Metrics systems
Mentor and support other team members, participate in design discussions and collaborate with the team
Be a part of on-call rotation and take ownership of the services you're running
What are we looking for in you?
You demonstrate a strong initiative and a preference for action, high level of responsibility, ownership and accountability
You prioritize customer needs, ensuring that our products are designed with the user in mind
You are able to take on complex challenges and break them down to achieve short feedback loops: to analyze, design, and build modular solutions, deliver MVPs, gather data and feedback and then progress iteratively
You have a strong problem solving mindset and have solid production debugging skills
You have excellent communication skills and the ability to work well within a team and across engineering teams in a fully remote environment
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
Requirements:
5+ years of relevant software development industry experience building and operating scalable, fault-tolerant, distributed systems
2+ years of software application development experience using Golang
Experience with at least one of the major Cloud Service Providers such as AWS, GCP or Azure
Experience with storing, shipping, and retrieving large volumes of data efficiently using technologies such as ClickHouse
Experience with technologies such as Kubernetes, Helm, ArgoCD, Temporal as well as infrastructure-as-code tools such as Terraform
Bonus Points:
Experience with ClickHouse
Experience writing Kubernetes operators or controllers
The typical starting salary for this role in the US is
$141,000
$208,000 USD
The typical sta ... (truncated, view full listing at source)
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