> Markdown version of [/jobs/ext/3978985-senior-software-engineer-data-platform](https://www.wearedevelopers.com/jobs/ext/3978985-senior-software-engineer-data-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer - Data Platform - **Company:** Nubank - **Location:** Berlin, Germany - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Systems Engineering, C++ (Programming Language), Databases, Data Architecture, Data Infrastructure, Distributed Data Store, Distributed Systems, Fault Tolerance, Identity and Access Management, Machine Learning, Open Source Technology, Software Systems, Value Engineering, Indexer, Backend, Event Driven Architecture, Build Management, Kubernetes, Storage Technologies, Apache Kafka, Data Management, Data Pipelines - **Published:** October 28, 2026 - **Apply:** https://startup.jobs/senior-software-engineer-data-platform-m-w-d-nubank-com-br-10601951 ## About the Role * Substantial experience designing, scaling and operating mission-critical distributed systems and backend architectures in high-throughput production environments. * Strong practical knowledge of container orchestration and systems management at scale, ideally Kubernetes internals and custom controllers or operators. * Advanced proficiency in a systems-oriented language such as Go, Java, Scala, Rust or C++. * Experience with database system architecture (storage engines, indexing, replication) and/or event-driven architectures using Apache Kafka. * A track record of technical leadership: writing design proposals, aligning teams on complex technical decisions, and mentoring engineers. Nice to have * Experience building internal developer platforms, custom compute engines or low-level database products. * Experience with data platforms or compute runtimes that support production AI/ML training and inference. * Familiarity with multi-region AWS networking, security, IAM and compute. * Involvement in open-source distributed systems projects (e.g. Kubernetes, Kafka, data orchestration)., Hybrid 2-3 times/week: Our hybrid work model brings us to the office at least twice a week, on strategic days designed to maximize team connection and collaboration. For more details, visit https://building.nubank.com/nu-hybrid-work-model/ Our working language is English. ## Description You will join an engineering squad in our Berlin office working on distributed systems and platform infrastructure. Our products serve analytics engineers and business teams across the company, but this is primarily a systems engineering role (roughly 75% core software systems engineering, 25% data architecture). We value engineering depth: we build internal distributed solutions and understand the runtimes underneath, rather than only orchestrating managed tools. As a Senior Software Engineer you will shape the architecture of our low-level infrastructure, orchestration frameworks and storage engines. You will lead technical design, resolve systemic bottlenecks in compute and streaming layers, and mentor engineers across squads, working with colleagues in Berlin, the US and Latin America. What you will do * Design and build core low-level services and distributed runtimes for Nubank's global data platform, with high fault tolerance, elastic scale and sub-second event availability. * Lead the design of compute orchestration frameworks on large Kubernetes clusters, improving scheduling throughput and resource utilization for complex data pipelines. * Design and optimize high-throughput streaming and storage architectures using Apache Kafka and distributed database internals for mission-critical financial workloads. * Find and remove performance, network and storage bottlenecks across the infrastructure stack to reduce latency. * Work with Analytics Engineering leads and platform users to define internal APIs, developer toolchains and data modeling practices that speed up developers company-wide. * Set standards for resilience testing, automated failover, observability and architectural documentation.