Software Engineer

The role #LI-MM1 We’re looking for a Software Engineer with strong C++ expertise to join the team building and operating Nebius Data Platform — a distributed storage and a processing platform that acts as the company’s “source of truth” and the backbone of many internal (and some external) products. Nebius Data Platform is a single multi-tenant ecosystem based on YTsaurus — instead of running separate HDFS/Kafka/HBase-style systems, we provide storage, compute, and analytics capabilities inside one platform. Built on top of the open-source YTsaurus ecosystem, we run and extend our own Nebius distribution and develop significant in-house functionality (core and platform-level). We can design, implement, and roll out features end-to-end on our clusters without waiting for upstream approvals and contribute upstream when it makes sense. At scale today, this includes~500 servers, ~20k CPU cores and ~10 PB of compressed data in our largest production cluster, supporting workloads ranging from business-critical pipelines and financial transactions to large-scale ML/LLM training datasets and compute. What’s inside the platform You’ll work on a system that includes (and ties together): 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). What you’ll do 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. Example projects 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. Tech stack Core: modern C++ (C++20, async + multithreaded primitives) Services & tooling: Go and Python (microservices, utilities, integration tests) What we expect 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. Nice to have 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.