Ververica GmbH
Tech / AI / Software
SeniorSoftwareEngineer-StreamStorage
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“Senior Software Engineer - Stream Storage at Ververica GmbH. Skills: distributed systems, storage engines, streaming systems, database internals, Apache Fluss. Design and implement distributed storage components for streaming tables. Work on table lifecycle: schema evolution, ingestion, compaction, retention, indexing”
Industry & Context.
Solve complex consistency and performance trade-offs
What They're Looking For.
Must Have
5+ years building distributed systems or storage systems, experience in Java, Go, Rust, or similar systems languages, Good understanding of: Consensus and replication (Raft, Paxos, etc.), Good understanding of: Storage engines (LSM trees, B-Trees, WAL, compaction), Good understanding of: Streaming systems (Kafka, Pulsar, Flink, etc.), Good understanding of: Transactional systems and consistency models, Experience debugging production distributed systems
Nice to Have
Experience with database internals or stream processing engines, Familiarity with table formats (Iceberg, Hudi, Delta, etc.), Contributions to open-source projects (better if ASF), Experience with Flink or streaming SQL engines
What You'll Do.
Design and implement distributed storage components for streaming tables
Work on table lifecycle: schema evolution
Enhance the Fluss Lakehouse ecosystem support
Contribute features and fixes to the Apache Fluss OSS project
Participate in design discussions and Fluss Improvement Proposals (FIPs)
Improve Fluss table engine performance and reliability
Enhance integration with streaming engines (e. g.
Build internal tooling and services on top of Fluss
Improve observability (metrics
Optimize production deployments
Contribute to benchmarking and testing frameworks
How You'll Work.
Team & Collaboration
Participate in design discussions; Engage with the open-source community via PR reviews and discussions; Collaborate with engineers passionate about distributed systems
Communication Scope
Engage with the open-source community via PR reviews and discussions
Process & Methodology
Fluss Improvement Proposals (FIPs)
Full Job Description
### About the Role We are building the next generation of stream-native storage systems centered around table semantics — not just logs. Our Stream Storage team develops high-performance distributed systems that power real-time analytics, streaming pipelines, and transactional workloads. As a Senior Software Engineer, you will contribute to core stream storage infrastructure, Apache Fluss (open-source), and internal production-grade systems built on Fluss. This role sits at the intersection of distributed systems, storage engines, streaming systems, and database internals. ### What You’ll Do ### Core Engineering * Design and implement distributed storage components for streaming tables * Work on table lifecycle: schema evolution, ingestion, compaction, retention, indexing * Enhance the Fluss Lakehouse ecosystem support * Contribute features and fixes to the Apache Fluss OSS project * Participate in design discussions and Fluss Improvement Proposals (FIPs) * Improve Fluss table engine performance and reliability * Enhance integration with streaming engines (e.g., Flink) * Engage with the open-source community via PR reviews and discussions ### Internal Platform Development * Build internal tooling and services on top of Fluss * Improve observability (metrics, logging, failure diagnostics) * Optimize production deployments * Contribute to benchmarking and testing frameworks **Requirements** ### What We’re Looking For ### Required Experience * 5+ years building distributed systems or storage systems * Strong experience in Java, Go, Rust, or similar systems languages * Good understanding of: * Consensus and replication (Raft, Paxos, etc.) * Storage engines (LSM trees, B-Trees, WAL, compaction) * Streaming systems (Kafka, Pulsar, Flink, etc.) * Transactional systems and consistency models * Experience debugging production distributed systems ### Strongly Preferred * Experience with database internals or stream processing engines * Familiarity with table formats (Iceberg,
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