ClickHouse Operations Engineer

present of AI; United States; Remote; USD 140,000 - 180,000; Full time

Job summary

PostHog is seeking an engineer to run and scale very large ClickHouse clusters, with automated provisioning, workload-aware hardware choices, and node-level tuning. The role leverages Terraform, Ansible, Kubernetes on AWS and strong Python tooling to manage performance at scale.

Ideal candidates will have deep ClickHouse internals knowledge, hands-on automation, and experience handling data at very large scale.

Qualifications

• Deep knowledge of ClickHouse internals and analytics databases.
• Experience automating infrastructure with Terraform and Ansible.
• Experience operating large-scale clusters on AWS and cloud infrastructure.
• Strong Python skills for tooling and automation.

Responsibilities

• Run and scale very large ClickHouse clusters with automated provisioning.
• Make hardware choices per workload and tune at the node level.
• Optimize query performance and monitor cluster health at scale.
• Contribute to incident response, capacity planning, and automation improvements.

Skills

ClickHouse internals

Terraform

Ansible

Kubernetes

AWS

Python

Cluster tuning

Tools

Terraform

Ansible

Kubernetes

AWS

Job description

The role centers on running and scaling very large ClickHouse clusters, including automated provisioning, hardware choices for each workload, and tuning at the node level. A strong candidate has gone deep into the internals of ClickHouse or similar analytics databases, and has automated infrastructure with Terraform, Ansible and Kubernetes on AWS. Experience handling data at very large scale, plus Python skills, rounds out the profile.

How it fits the AI era

AI tools can help draft infrastructure code, spot slow queries and sift through performance data, which speeds up routine operations. The company also positions its data as something that people and AI agents query, so database load and query patterns may become less predictable. Judgment on hardware tradeoffs, capacity planning and incident response stays with the engineer.

How it builds AI experience

The work supports a platform where AI agents and AI observability tools read and act on product data, so the database layer has to hold up under that kind of query traffic. Building a query optimizer and tuning clusters for varied workloads gives hands-on exposure to the data infrastructure behind AI features. Someone new to this can build the base by running a ClickHouse cluster of their own and testing how automated or agent-generated queries affect it.

Worth showing

• ClickHouse internals knowledge
• Terraform and Ansible automation
• Large-scale cluster operations
• Query performance tuning

This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.

About PostHog

All-in-one product analytics, session replay, and feature management platform for engineering teams.