Backend Infrastructure Engineer

FELDERA, INC.
United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Application Programming Interfaces (APIs) Apache HTTP Server C++ (Programming Language) Computer Programming Databases Data Integration Data Loss Data Migration Serialization Software Debugging Distributed Systems
+13 more
Fault Tolerance Protocol Buffers JSON PostgreSQL Online Analytical Processing Online Transaction Processing Parquet Change Data Capture Data Lakes Avro Apache Kafka Stream Processing Golang

Job description

We’re looking for a Rust backend engineer to own and evolve Feldera’s connector ecosystem. You’ll build and maintain connectors with systems like Delta Lake, Apache Iceberg, Kafka, and Postgres. This means working deep in the details of each system’s storage formats, wire protocols, transactional semantics, and change-data-capture mechanisms, and turning that into ingest and output adapters that are fast, correct, and resilient to failure., * Connector engineering: Own and evolve Feldera’s input and output connectors for data lakes (Delta Lake, Iceberg), streaming systems (Kafka and the broader Kafka ecosystem), and databases (Postgres and other OLTP/OLAP stores).

  • Change data capture: Build robust CDC ingestion that turns upstream changes into correct, ordered, and consistent change streams into Feldera pipelines.
  • Connector framework: Design and improve the shared abstractions, APIs, and tooling that make authoring, testing, and operating connectors fast and consistent.
  • Formats & protocols: Work at the level of table formats (Parquet, Delta, Iceberg metadata), serialization formats (Avro, JSON, Protobuf), and wire protocols to integrate cleanly and efficiently with each system.
  • Correctness & fault-tolerance: Ensure connectors are reliable and operate without data loss or duplication beyond stated guarantees.
  • Performance: Push connector throughput and latency to keep pace with demanding production workloads.
  • Troubleshooting: Debug complex distributed systems issues spanning Feldera and external systems in customer environments., * Fully remote. Distributed across the U.S. and abroad. We hire for timezone overlap, not location.
  • Flat organization with high autonomy, ownership and asynchronous collaboration. You’ll work directly alongside the founders.
  • Fast and honest. We move quickly, decide based on evidence, course-correct openly, and expect you to do the same.
  • Rewarded for impact, not tenure. We recognize what you ship, the outcomes it drives, and how much you raise the team’s ceiling.

Requirements

  • Strong proficiency in Rust, or strong systems-programming experience in a comparable language (C++, Go, Java/Scala) with a demonstrated ability to ramp quickly on Rust.
  • Experience building data integrations, connectors, or pipelines in production - moving data between storage systems, streaming platforms, or databases.
  • Hands-on experience with one or more of: Kafka, Delta Lake, Iceberg, Postgres, or comparable streaming/lakehouse/database systems.
  • Working knowledge of data serialization and table formats (e.g. Avro, Protobuf, JSON, Parquet).
  • Understanding of distributed-systems fundamentals: delivery semantics, ordering, checkpointing, and fault recovery.
  • Strong troubleshooting skills and the ability to debug complex issues across system boundaries.
  • Self-directed with excellent communication skills and the ability to work effectively in a remote team.

Candidates must have authorization to work in their country of residence. We are unable to sponsor employment visas at this time.

Benefits & conditions

  • Competitive salary & meaningful equity
  • Medical, dental & vision - 90% of premiums covered by Feldera
  • HSA & FSA
  • 401(k)
  • Fully remote

About the company

Feldera is redefining how engineers compute over changing data. Powered by an award-winning breakthrough in database theory (DBSP), our platform incrementally maintains even the most complex SQL views as data changes, even when pipelines have hundreds of joins, aggregates, unions, and even recursion. It has allowed leading enterprises to have always-on real-time insights over both live and historical data, with 10x lower cost and 100x faster time-to-production.

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