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Senior Technical Customer Support Engineer - Australia

ClickHouse - Remote - Remote - posted 2026-08-10

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ClickHouse, a Forbes Cloud 100 company and leader in real-time analytics and data warehousing, is seeking a Senior Technical Customer Support Engineer to join its global support team. This remote role is based in Australia and serves customers across APJ, APAC, and EMEA regions. You will be the technical face of ClickHouse to customers and prospects, handling support interactions via chat, calls, Slack, and video meetings. Your responsibilities include triaging and resolving support tickets, engaging with the user community, supporting pre- and post-sales activities, partnering with the Go-To-Market team on technically complex POCs, and driving improvements to support processes. Key responsibilities: - Support ClickHouse users, customers, and prospects across multiple channels (cases, chat, Slack, community, meetings) - Develop and share solutions via documentation, knowledge base, blogs, meetups, webinars, and training - Collaborate with global Support Services, Engineering, Go-to-Market, and Product Management teams - Mentor and train colleagues, users, and customers - Deliver professional, timely responses within SLAs and maintain on-call coverage as required - Build strong relationships with colleagues, customers, and partners Required qualifications: - Technical expertise in ClickHouse (open-source or Cloud), SQL databases, OLAP, cloud-native SaaS, or distributed systems - Previous experience as a Support Engineer, Consultant, Database Administrator, SRE, Solutions Engineer, Software Engineer, or Systems Engineer - Availability for 24x7 global support scheduling - Strong written and verbal English communication - Ability to work fully remote with reliable connectivity - Teamwork mindset, empathy, and problem-solving orientation - Self-driven, curious, and committed to continuous learning Bonus qualifications include ClickHouse experience, open-source involvement, cloud platform experience (Azure, GCP, AWS), and familiarity with data pipeline tools (Kafka, Kinesis, Spark, RabbitMQ).

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