About the team

The Integrations Ecosystem org is the bridge between ClickHouse and the rest of the data world. We build and maintain the connections that make ClickHouse accessible to the developers, data engineers, and analysts who rely on it in production every day. Our scope spans low-level database drivers, ingestion and CDC pipelines, data framework integrations, and BI connectivity — ensuring ClickHouse feels native in whatever stack our users already have.

We maintain the official language clients (Python, JavaScript, Java, Go, Rust, C++, C#) and ODBC driver; ship first-party connectors for Kafka Connect, Apache Spark, Apache Flink, dbt, and Airbyte; and own integrations with BI platforms.

This role sits on the Language Clients team, which provides the JVM foundation that everything else in the ecosystem is built on.

What you'll do

As a Senior Software Engineer on Language Clients, you'll be a technical owner of ClickHouse's Java client and JDBC driver, the foundation that our own Connectors team and a long list of external

frameworks rely on to talk to ClickHouse.

Your primary users are engineers: the Connectors team building ClickHouse connectors for Kafka, Flink, Spark, and others, and the broader JVM ecosystem (data ingestion tools, BI platforms, data visualizations) that consumes the driver directly. Your job is to make sure they have a fast, reliable, well-designed foundation and to treat their feedback as the signal for where the driver goes next.

In your first year you can expect to:

• Own the Java client and JDBC driver end-to-end: roadmap, API design, performance, release engineering, and partner-facing support.
• Drive throughput and latency work across the client and ClickHouse server
• Partner day-to-day with the Connectors team as an embedded internal customer: understand what their connectors need from the driver, and ship it.
• Engage directly with external partners across data ingestion, and data visualization on interoperability, regressions, and roadmap alignment.
• Ship visible, measurable wins in throughput, stability, and developer experience.

We expect you to bring opinions, artifacts, and written proposals to shape where we invest next.

About you

• 5+ years of software engineering experience with a significant portion focused on data-intensive systems: drivers, SDKs, ingestion, CDC, streaming, or analytics.
• Deep Java and JVM expertise: memory model, GC tuning, profiling, and the ability to reason about throughput and latency at the level of bytes on the wire.
• Hands-on experience building or substantially extending a library that other engineers depend on. You understand that API design compounds, and that a breaking change in a widely used library is a very different thing from a breaking change in an application.
• Strong grasp of database fundamentals: SQL, query execution, and analytical/OLAP workloads. Judgment about when to lean on framework abstractions versus when to drop down to the protocol.
• Solid instincts on concurrency in the JVM: executors, reactive streams, backpressure, connection pooling, and the failure modes that come with each.
• Thoughtful, transparent use of modern AI development tools (Claude Code, Cursor, Copilot, or equivalents) combined with strong independent design and code review judgment. We expect engineers to lean on AI where it's genuinely helpful and to be explicit about where they didn't. Resistance to AI tooling is a mismatch for this team and so is over-reliance without the underlying engineering depth to review what comes out.
• Excellent written communication. Most of our coordination happens in design docs, PR descriptions, and RFCs.
• Genuine open-source disposition: comfort engaging with community issues, external contributors, and public design discussions. You don't need to be a maintainer of a well-known project, but you do need to be comfortable working in the open.

Nice to have

• Working knowledge of JDBC internals, ADBC, or Arrow / Arrow Flight SQL.
• Experience designing or evolving wire protocols, or contributing to a widely-used network client.
• Prior contributions to open-source data infrastructure (Kafka, Spark, Flink, dbt, Debezium, Iceberg, or similar).
• Working knowledge of ClickHouse or another columnar/OLAP engine.