Senior Software Engineer - Data Integration & JVM Ecosystem
ClickHouseGermany (Remote)Posted 9 March 2026
Job Description
About ClickHouse
Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 3,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.
The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.
We’re on a mission to transform how companies use data. Come be a part of our journey!
The Connectors team is the bridge between ClickHouse and the entire data ecosystem. We build and maintain the connectors that make ClickHouse accessible to millions of developers and data practitioners worldwide. Our work spans from low-level database integrations to high-level data visualization plugins, ensuring that ClickHouse seamlessly integrates with the tools our users already know and love.
We're responsible for the official data connectors (Kafka, dbt, Spark, Flink, Beam, Fivetran), and integrations with leading visualization platforms (Grafana, Tableau, Power BI, Metabase).
What will you do?
As a Senior Software Engineer specializing in JVM-based frameworks, you'll serve as a core contributor, owning and maintaining critical parts of ClickHouse's Data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience, where you'll craft tools that enable Data Engineers to harness ClickHouse's incredible speed and scale.
You'll own the full lifecycle of data framework integrations - from the core database driver that handles billions of records per second , to SDKs and connectors that make ClickHouse feel native in JVM-based applications. This isn't just about writing code; you're building the foundation that thousands of Data engineers rely on for their most critical data workloads.
Your work will directly impact how companies process massive datasets, from real-time analytics platforms ingesting millions of events per second to observability systems monitoring global infrastructure. You'll collaborate closely with the open-source community, internal teams, and enterprise users to ensure our JVM integrations set the standard for performance, reliability, and developer experience.
About you:
6+ years of software development experience focusing on building and delivering high-quality, data-intensive solutions.
Proven experience with the internals of at least one of the following technologies: Apache Spark, Apache Flink, Kafka Connect, or Apache Beam.
Experience developing or extending connectors, sinks, or sources for at least one big data processing framework such as Apache Spark, Flink, Beam, or Kafka Connect.
Strong understanding of database fundamentals : SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases.
A track record of building scalable data integration systems (beyond simple ETL jobs)
Strong proficiency in Java and the JVM ecosystem, including deep knowledge of memory management, garbage collection tuning, and performance profiling.
Solid experience with concurrent programming in Java, including threads, executors, and reactive or asynchronous patterns.
Outstanding written and verbal communication skills to collaborate effectively within the team and across engineering functions.
Understanding of JDBC , network protocols (TCP/IP, HTTP), and techniques for optimizing data throughput over the wire.
Passion for open-source development.
Bonus points for:
Prior contributions to open-source projects: actively engaging with the OSS community, advocating for users, and influencing the evolution of the core sy ... (truncated, view full listing at source)
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