Senior Software Engineer

Role overview

Join ClickHouse as a Senior Software Engineer on the Connectors team. You will build and maintain critical integrations that help developers and data practitioners access ClickHouse, directly influencing how organizations process massive datasets.

Key missions

• Own and maintain critical parts of the ClickHouse data engineering connectors ecosystem.
• Manage the end-to-end integration lifecycle across data frameworks, from the core database driver to SDKs and connectors.
• Collaborate with the open-source community, internal teams, and enterprise users to ensure JVM-based integrations meet high standards for performance, reliability, and developer experience.

Responsibilities

• Develop and extend connectors, sinks, and sources for data processing frameworks.
• Work on performance and reliability improvements, including database and data-plane optimizations.
• Contribute to integration tooling and quality through scalable, production-ready engineering.

Requirements

• Experience building or extending connectors/sinks/sources for at least one big data framework: Apache Spark, Apache Flink, Apache Beam, or Kafka Connect.
• 6+ years of software development focused on high-quality, data-intensive solutions.
• Proven internals knowledge of at least one of: Apache Spark, Apache Flink, Kafka Connect, or Apache Beam.
• Strong database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases.
• Understanding of JDBC, network protocols (TCP/IP, HTTP), and techniques to optimize data throughput over the wire.
• Strong proficiency in Java and the JVM ecosystem, including memory management, GC tuning, and performance profiling.
• Excellent written and verbal communication.
• Track record building scalable data integration systems (beyond basic ETL jobs).
• Concurrency experience in Java (threads, executors, reactive/asynchronous patterns).
• Passion for open-source and prior OSS contributions.

Nice to have

• Familiarity with ClickHouse or similar high-performance data platforms.
• Working knowledge of Python in data engineering contexts (e.g., Pandas, PySpark, Airflow) and ability to contribute to Python tooling.