Senior Software Engineer - Data Integration & Jvm Ecosystem

ClickHouse ClickHouse · Data AI · Israel +2 · Engineering

Senior Software Engineer focused on JVM-based frameworks to build and maintain data connectors and integrations for ClickHouse, enabling data engineers to process massive datasets and work with real-time analytics and observability systems. The role involves owning the full lifecycle of data framework integrations, from core database drivers to SDKs and 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.
  • Strong understanding of database fundamentals
  • A track record of building scalable data integration systems (beyond simple ETL jobs)