Senior Software Engineer - Data Integration & Jvm Ecosystem

ClickHouse ClickHouse · Data AI · Israel +2 · Engineering

Senior Software Engineer focused on JVM-based data integration and the JVM ecosystem for ClickHouse. This role involves owning and maintaining critical parts of ClickHouse's data engineering ecosystem, bridging high-performance database engineering with developer experience. Responsibilities include crafting tools for Data Engineers, owning the full lifecycle of data framework integrations (core database drivers, SDKs, connectors), and collaborating with the open-source community and enterprise users.

What you'd actually do

  1. 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.
  2. You'll own the full lifecycle of data framework integrations - from the core database driver that [handles billions of records per second](https://www.linkedin.com/feed/update/urn:li:activity:7265414437384187904/), to SDKs and connectors that make ClickHouse feel native in JVM-based applications.
  3. 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.
  4. 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.
  5. 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.

Skills

Required

  • 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.

Nice to have

  • Prior contributions to open-source projects: actively engaging with the OSS community, advocating for users, and influencing the evolution of the core system through your contributions.
  • Familiarity with ClickHouse or similar high-performance data platforms.
  • Working knowledge of Python, especially in data engineering contexts (e.g., Pandas, PySpark, Airflow), and ability to contribute to Python tooling when needed.

What the JD emphasized

  • Proven experience with the internals of at least one of the following technologies: Apache Spark, Apache Flink, Kafka Connect, or Apache Beam.
  • A track record of building scalable data integration systems (beyond simple ETL jobs)