Staff Data Engineer
PostscriptFull Time
Expert & Leadership (9+ years)
Candidates should have 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. 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. Understanding of JDBC, network protocols (TCP/IP, HTTP), and techniques for optimizing data throughput over the wire. Passion for open-source development. Prior contributions to open-source projects, familiarity with ClickHouse or similar high-performance data platforms, and working knowledge of Python are considered bonus points.
As a Senior Software Engineer specializing in JVM-based frameworks, you will serve as a core contributor, owning and maintaining critical parts of ClickHouse's Data engineering ecosystem. You will craft tools that enable Data Engineers to harness ClickHouse's incredible speed and scale. You will own the full lifecycle of data framework integrations, from the core database driver to SDKs and connectors. You will 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.
High-speed column-oriented database management system
ClickHouse provides a high-speed, column-oriented database management system designed for developers and businesses that manage large-scale data. Its primary product processes analytical queries quickly by storing data from the same columns together, making it significantly faster than traditional row-oriented databases, especially in Online Analytical Processing (OLAP) scenarios. ClickHouse stands out from competitors by offering a free, open-source database that can be deployed on local machines or in the cloud, along with a fully managed service on platforms like AWS, GCP, and Microsoft Azure. The company's goal is to deliver a cost-effective solution that simplifies data management for its clients, as evidenced by user feedback highlighting substantial cost savings.