Senior Cloud Data Infrastructure Engineer ; Remote

United States (Remote)

Recognized on the 2025 Forbes Cloud 100 list, Click House is one of the most innovative and fast-growing private cloud companies. With over 2,000 customers and ARR that has more than quadrupled over the past year, Click House leads the market in real-time analytics, data warehousing, observability, and AI workloads. Click House’s $400M Series D financing round confirms our momentum. We’re on a mission to transform how companies use data.

Come be a part of our journey!

The Cloud Auto Scaling team is dedicated to implementing robust vertical and horizontal auto-scaling capabilities within the Click House cloud environment. We seek exceptional software engineers to develop and maintain the auto-scaling infrastructure to transform Click House into a fully functional serverless database solution. Collaborating closely with the core database team, we are evolving Click House into a cloud-native database system and engaging with other cloud teams to drive continuous improvements in cloud infrastructure for performance and scalability.

• Build a cutting-edge cloud-native database platform on top of the public cloud.
• Work on autoscaling and our in-house Kubernetes operator to support seamless Vertical and Horizontal Auto-scaling.
• Improve the metrics pipeline and build algorithms to generate better autoscaling statistics and recommendations.
• Collaborate with the Click House core development team and other data plane teams to support auto-scaling use cases and other infrastructure improvements.
• Architect and build a robust, scalable, and highly available distributed infrastructure.

• 5+ years of relevant software development experience building and operating scalable, fault-tolerant distributed systems.
• Experience building operators with Kubernetes and controller runtime.
• Production experience with programming languages like Go, C++, or Java.
• On-call experience (e.g., Pager Duty) and strong debug/problem-solving skills in production environments.
• Expertise with a public cloud provider (AWS, GCP, Azure) and their IaaS offerings (e.g., EC2).
• Experience with Data Storage, Ingestion, and Transformation (Spark, Kafka or similar tools).
• You are passionate about solving data problems at scale.
• Experience with Python (uvicorn, FastAPI) and data science libraries (Pandas, Num Py) is a plus.
• Excellent communication skills and ability to work well within and across engineering teams.

The typical starting salary for this role in the US is $133,450 - $197,200 USD
.

The typical starting salary for this role in US Premium Markets is $157,000 - $232,000 USD
.

For roles based in the United States, the typical starting salary range is listed above. In certain locations (e.g., San Francisco Bay Area and New York City Metro Area), a premium market range may apply.

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, and ranges may be adjusted in the future. An individual’s placement within the range depends on factors such as education, qualifications, certifications, experience, skills, location, performance, and business needs.

• Flexible work environment – Click House is globally distributed and remote-friendly. We operate in 20 countries.
• Healthcare – Employer contributions towards healthcare.
• Equity – Stock options for new team members.
• Time off – Flexible time off in the US; generous entitlement in other countries.
• A $500 Home office setup – for remote employees.
• Global Gatherings – Opportunities to engage with colleagues at company-wide offsites.

As part of our first 500 employees, you will be instrumental in shaping our culture.

Learn more about our values, blog posts, or follow us on Linked In to see what’s happening at Click House.

Click House provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type based on factors such as race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by law.

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Public information and disclosures related to equal opportunity are provided in accordance with applicable law.