ClickHouse Expert / Senior Data Engineer (Cloud Billing Analytics)

Overview

We are undertaking a major architectural shift: we are moving our cloud-billing analytics engine to ClickHouse to support real-time analytics for AWS, Azure, GCP, and AI workloads. This migration is central to our next stage of product evolution, and we are looking for a world-class ClickHouse expert to lead this transition end-to-end.

If you’ve built or operated ClickHouse at large scale — or you’ve always wanted to apply that skill set to one of the largest cloud-billing datasets in the industry — this is the role.

As nOps continues to grow, we now process over $3B in annualized cloud spend for fast-growing SaaS companies, enterprises, and private-equity portfolios.

Our existing analytics engine is powerful, but it is reaching the limits required for:

-Massive ingestion volumes across AWS, Azure, GCP, and AI model usage

• High-speed cost allocation for multi-cloud, multi-team, multi-account organizations
• Real-time anomaly detection on billions of events
• Interactive slicing/dicing of historical billing at sub-second response times

We are looking deep ClickHouse specialist to architect, migrate, optimize, and productionize this system.

What You Will Own:

• Lead the ClickHouse Migration
• Design the end-to-end architecture for nOps’ new ClickHouse-based analytics engine
• Drive the migration of billing pipelines, data models, and analytical workloads into ClickHouse
• Define ingestion patterns, storage formats, sharding/replication strategies, and schema designs

Operate & Scale ClickHouse in Production

• Optimize query patterns, table engines, partitioning, compression, indexes
• Implement observability, alerting, failover, backups, and disaster recovery
• Build the Analytics Foundation for $3B+ in Cloud Spend
• Enable fast cost allocation queries
• Power real-time anomaly detection
• Support ML pipelines, predictive forecasting, and FinOps automation
• Work directly with founders, product, engineering, and FinOps leaders

Required Expertise

-Deep hands-on experience running ClickHouse in production — large-scale preferred
-Strong understanding of OLAP systems, distributed columnar storage, and analytical databases
-Proven ability to model massive datasets (billions of rows, TB–PB scale)
-Expertise with performance tuning, partitioning, sharding, replication, and query optimization
-Strong SQL and data modeling fundamentals
-Experience building ETL/ELT ingestion pipelines

• Comfortable with infrastructure-as-code (Terraform, Ansible, Kubernetes)

Nice to Have
-Experience with cloud billing datasets (AWS CUR, Azure EA, GCP Billing Export)
-Background in FinOps, cost allocation, unit economics, or usage analytics
-Experience supporting data science, ML, or agentic workflows