About HighLevel: HighLevel is a cloud-based, all-in-one white-label marketing and sales platform that empowers marketing agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. With a focus on streamlining marketing efforts and providing comprehensive solutions, HighLevel helps businesses of all sizes achieve their marketing goals. We currently have ~1200 employees across 15 countries, working remotely as well as in our headquarters, which is located in Dallas, Texas. Our goal as an employer is to maintain a strong company culture, foster creativity and collaboration, and encourage a healthy work-life balance for our employees wherever they call home. Our Website - https://www.gohighlevel.com/ YouTube Channel - https://www.youtube.com/channel/UCXFiV4qDX5ipE-DQcsm1j4g Blog Post - https://blog.gohighlevel.com/general-atlantic-joins-highlevel/ Our Customers: HighLevel serves a diverse customer base, including over 60K agencies & entrepreneurs and 500K businesses globally. Our customers range from small and medium-sized businesses to enterprises, spanning various industries and sectors. Scale at HighLevel: We operate at scale, managing over 40 billion API hits and 120 billion events monthly, with more than 500 micro-services in production. Our systems handle 200+ terabytes of application data and 6 petabytes of storage. About the Role: We are seeking a highly skilled Senior Database Engineer with expertise in ClickHouse and other columnar databases. The ideal candidate will have a deep understanding of database performance optimization, query tuning, data modeling, and large-scale data processing. You will be responsible for designing, implementing, and maintaining high-performance analytical databases that support real-time and batch processing. Responsibilities:

Design, optimize, and maintain ClickHouse databases to support high-throughput analytical workloads

Develop and implement efficient data models for fast query performance and storage optimization

Monitor and troubleshoot database performance issues, ensuring minimal downtime and optimal query execution

Work closely with data engineers, software developers, and DevOps teams to integrate ClickHouse with data pipelines

Optimise data ingestion processes, ensuring efficient storage and retrieval of structured and semi-structured data

Implement partitioning, sharding, and indexing strategies for large-scale data processing

Evaluate and benchmark ClickHouse against other columnar databases such as Apache Druid, Apache Pinot, or Snowflake

Establish best practices for backup, replication, high availability, and disaster recovery

Automate database deployment, schema migrations, and performance monitoring using infrastructure-as-code approaches

Requirements:

5+ years of experience working with high-performance databases, with a focus on ClickHouse or similar columnar databases

Strong knowledge of SQL, query optimisation techniques, and database internals

Experience handling large-scale data (TBs to PBs) and optimizing data storage & retrieval

Hands-on experience with ETL/ELT pipelines, streaming data ingestion, and batch processing

Proficiency in at least two scripting/programming languages like NodeJS, Python, Go, or Java for database automation

Familiarity with Kafka, Apache Spark, or Flink for real-time data processing

Experience in Kubernetes, Docker, Terraform, or Ansible for database deployment & orchestration is a plus

Strong understanding of columnar storage formats (Parquet, ORC, Avro) and their impact on performance

Knowledge of cloud-based ClickHouse deployments (AWS, GCP, or Azure) is a plus

Excellent problem-solving skills, ability to work in a fast-paced environment, and a passion for performance tuning

Preferred Skills:

Experience with alternative columnar databases like Apache Druid, Apache Pinot, or Snowflake

Background in big data analytics, time-series databases, or high-performance data warehousing

Prior experience working with distributed systems and high-availability architectures