You'll own the full lifecycle of data framework integrations – from the core database driver that handles billions of records per second, to SDKs and connectors that make us feel native in JVM-based applications. 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.
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. 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.
About you:
6+ years of software development experience focusing on building and delivering high-quality, data-intensive solutions.
Proven experience with the internals of streaming or data integration frameworks, with strong preference for Apache Kafka (or similar pub/sub systems), Kafka Connect, Apache Flink or Apache Beam.
Experience developing or extending connectors, sinks, or sources for at least one streaming processing framework such as Apache Flink, Beam, or Kafka Connect, with preference for experience building or maintaining production-grade streaming connectors.
Hands-on experience with Apache Kafka or similar distributed messaging systems (e.g., Pulsar, Kinesis), including topic design, consumer groups, and performance tuning.
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.
Passion for open-source development.
Bonus points for:
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 – big advantage.
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.
