Senior Software Engineer (Data Platform, C++) - Nebius

Distributed Storage (Cypress) : transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations. Compute & ETL : a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering. Interactive analytics (CHYT) : ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place. Dynamic Tables : low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores. Orchestracto : workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native). Design and implement new functionality in YTsaurus core (C++) with production reliability in mind. Build and evolve platform-level capabilities: platform architecture and operating model-multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases. Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation. Own production quality: incident response / on-call rotation , root cause analysis, and turning learnings into durable fixes. Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10-100x cluster growth . Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection. Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows. Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability. Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths. Core: modern C++ (C++20, async + multithreaded primitives) Services & tooling: Go and Python (microservices, utilities, integration tests) 5+ years of software engineering experience. Strong C++ skills (you’ll write core code). Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them). Experience developing and/or operating high-load, distributed services . Production mindset: ability to use SSH, read logs/metrics/traces , and debug distributed systems behavior. Solid CS fundamentals: algorithms, data structures, concurrency basics. Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems). Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering. Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs). Competitive compensation Career growth and learning opportunities Flexibility and work-life balance Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams

We’re looking for engineers who combine strong systems skills with product sense : understanding who uses the platform, why certain capabilities matter, and making pragmatic trade-offs to maximize impact. On our team, engineering work is expected to be connected to real users and outcomes - you’ll regularly align with internal stakeholders, clarify requirements, and help drive prioritization. In this role, you will: Design and implement new functionality in YTsaurus core (C++) with production reliability in mind. Build and evolve platform-level capabilities: platform architecture and operating model-multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases. Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation. Own production quality: incident response / on-call rotation , root cause analysis, and turning learnings into durable fixes. Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10-100x cluster growth . Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection. Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows. Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability. Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths. Core: modern C++ (C++20, async + multithreaded primitives) Services & tooling: Go and Python (microservices, utilities, integration tests) 5+ years of software engineering experience. Strong C++ skills (you’ll write core code). Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them). Experience developing and/or operating high-load, distributed services . Production mindset: ability to use SSH, read logs/metrics/traces , and debug distributed systems behavior. Solid CS fundamentals: algorithms, data structures, concurrency basics. Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems). Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering. Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs). We conduct coding interviews as part of the process. Benefits & Perks: Competitive compensation Career growth and learning opportunities Flexibility and work-life balance Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.

Distributed Storage (Cypress) : transactional semantics, tiered storage, erasure coding, replication, and strong reliability expectations. Compute & ETL : a cluster-wide job scheduler (tens of thousands of cores), MapReduce, YQL for SQL-like data processing, and SPYT (Spark over YTsaurus) for modern data engineering. Interactive analytics (CHYT) : ClickHouse® instances spun up directly on compute nodes for fast SQL over data in-place. Dynamic Tables : low-latency NoSQL KV with distributed ACID transactions for OLTP-style workloads and feature stores. Orchestracto : workflow orchestration deeply integrated with the platform (Airflow-like, but platform-native). Design and implement new functionality in YTsaurus core (C++) with production reliability in mind. Build and evolve platform-level capabilities: platform architecture and operating model-multi-cluster growth, shared primitives, and a consistent experience that scales with new teams and use cases. Improve end-to-end platform experience for internal (and external-facing) users: APIs, guardrails, debugging workflows, and automation. Own production quality: incident response / on-call rotation , root cause analysis, and turning learnings into durable fixes. Roll out sharded YTsaurus masters (incl. Kubernetes operator support) and build automatic balancing of metadata across master cells (consensus groups) to remove control-plane bottlenecks and unlock 10-100x cluster growth . Make CHYT interactive SQL faster and more predictable at high load via performance work like data-skipping / min-max-style indexes and improved execution introspection. Turn Orchestracto into a platform product by defining the building blocks, developer experience, and governance for how teams create and share workflows. Scale and harden Parquet-on-S3 for native YTsaurus workloads by tackling replication/movement, consistent lifecycle semantics, and master-server metadata optimizations for performance and reliability. Design and ship complete, trustworthy audit trails for data changes (who/what/when) across heterogeneous storage and compute paths. Core: modern C++ (C++20, async + multithreaded primitives) Services & tooling: Go and Python (microservices, utilities, integration tests) 5+ years of software engineering experience. Strong C++ skills (you’ll write core code). Working knowledge of Python and/or Go (you don’t have to be expert, but should be comfortable navigating them). Experience developing and/or operating high-load, distributed services . Production mindset: ability to use SSH, read logs/metrics/traces , and debug distributed systems behavior. Solid CS fundamentals: algorithms, data structures, concurrency basics. Experience with Big Data systems (YTsaurus/Hadoop/Spark/ClickHouse/Kafka-like ecosystems). Experience with multi-tenant platforms, schedulers, resource isolation, quotas, and reliability engineering. Strong performance engineering skills (profiling, lock contention, latency/throughput tradeoffs). Competitive compensation Career growth and learning opportunities Flexibility and work-life balance Collaborative and innovative culture Opportunity to work on impactful AI projects International environment and talented teams