Senior Software Engineer (Java Streaming, Connectors)

Role overview

Join ClickHouse as a Senior Software Engineer focused on Java/JVM streaming and connectors. You’ll be a core contributor to ClickHouse’s data engineering ecosystem, owning critical pieces that help data teams process massive datasets with high performance and reliability.

Key missions

• Own and maintain critical parts of ClickHouse’s data engineering ecosystem for JVM-based frameworks.
• Build and maintain the full lifecycle of data framework integrations, from:
  • the core database driver handling billions of records per second
  • to SDKs and connectors that make ClickHouse feel native in JVM applications
• Collaborate with the open-source community, internal teams, and enterprise users to set standards for performance, reliability, and developer experience.

Responsibilities

• Deliver high-quality, data-intensive solutions and integration tooling.
• Ensure connector/SDK performance and reliability, including end-to-end throughput over the network.
• Contribute to the evolution of JVM integration components through active open-source engagement.

Requirements

• Database fundamentals: SQL, data modeling, query optimization; experience with OLAP/analytical databases.
• Proven internals experience with at least one of:
  • Apache Spark, Apache Flink, Kafka Connect, Apache Beam
• Experience developing/extending connectors, sinks, or sources for at least one of those frameworks.
• 6+ years of software development experience building data-intensive solutions.
• Strong communication skills and collaboration across engineering and with users.
• Strong concurrent programming in Java (threads, executors, reactive/asynchronous patterns).
• Deep JVM expertise: memory management, GC tuning, and performance profiling.
• Understanding of JDBC, network protocols (TCP/IP, HTTP), and optimizing data throughput over the wire.
• Prior open-source contributions and community engagement.
• Familiarity with ClickHouse or similar high-performance data platforms.

Nice to have

• Working knowledge of Python in data engineering contexts (e.g., Pandas, PySpark, Airflow) and ability to contribute to Python tooling.