Senior Software Engineer (Stream Processing)

The role

We are looking for a Senior Software Engineer to build the event-processing pipelines and services that turn Nebius product usage into revenue.
You will work on systems that process a continuous stream of usage events, where correctness and failure recovery matter as much as throughput. The output is money: a silently dropped or double-counted event is a real financial error.
Usage of every Nebius product arrives as a stream of events. Our pipelines and services ingest, validate, enrich and price it in near real time, and deliver the results to invoicing, reporting and customer-facing account management.

In this role, you will:

• Build stateful streaming pipelines that compute billed consumption in near real time.


• Develop and operate Go services that ingest usage events, move data between our storage systems and deliver consumption data to users through usage APIs and billing data exports.


• Guarantee correctness under failures: idempotency, exactly-once processing and reconciliation.


• Operate transactional storage, persistent queues and change data capture under high throughput.


• Build reusable streaming infrastructure rather than solving each use case independently.


• Improve the reliability, scalability, latency and observability of the billing platform.


• Take end-to-end ownership of your systems: design, implementation, reliability and deployment.

We expect you to have:

• Strong software engineering fundamentals.


• Professional experience building and operating backend, streaming or data-intensive systems.


• The ability to reason about consistency and data correctness under failures.


• Experience with databases, messaging systems or event-processing platforms.


• The ability to investigate unfamiliar systems and solve problems without an obvious predefined solution.


• The ability and willingness to learn the team's technology stack.

It will be an added bonus if you have:

• Experience with a stateful stream-processing framework such as Apache Flink or Kafka Streams.


• Experience designing streaming pipelines.


• Go development experience.


• Experience operating services in Kubernetes.

Technology stack

• Go, Python


• Apache Flink


• YDB


• YTsaurus


• Messaging and event-streaming systems


• Kubernetes
  
  

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