👋🏼 We're Nagarro. We are a digital product engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (18 000+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in! By this point in your career, it is not just about the tech you know or how well you can code. It is about what more you want to do with that knowledge. Can you help your teammates proceed in the right direction? Can you tackle the challenges our clients face while always looking to take our solutions one step further to succeed at an even higher level? Yes? You may be ready to join us.

We are looking for a Senior Rust Data Engineer who can lead the architecture and scaling of high-throughput data services, ingestion pipelines, and resilient API contracts. Leveraging Rust, you will build ultra-low-latency, memory-efficient data infrastructure and integrate it seamlessly with enterprise cloud warehouses and lakehouses.

Responsibilities:

• Lead the architecture and scaling of high-throughput data services and ingestion pipelines.
• Build high-performance, low-latency data infrastructure using Rust.
• Design resilient APIs, data contracts, and schemas.
• Integrate data services with cloud warehouses and lakehouse platforms.
• Optimize distributed data processing, storage, caching, and query performance.
• Drive technical architecture and best practices for scalable data platforms.

• 8+ years of experience in software/data engineering.
• Proven background delivering robust, distributed systems and large-scale data platforms in production.
• Production Rust: Strong, hands-on experience building multi-threaded, asynchronous services in Rust, with deep knowledge of memory management and concurrency patterns.
• Contract-Driven API Design: Extensive experience establishing data contracts and schemas using Protobuf/gRPC, Avro, or OpenAPI, including backward compatibility and schema evolution strategies.
• Cloud & Warehouse Mastery: Deep expertise in at least one major cloud provider (AWS, GCP, Azure) and production mastery of at least one enterprise analytical platform:
  Snowflake, Google BigQuery, Databricks (Delta Lake), or AWS Glue/Redshift.
• Distributed Data Fundamentals: Advanced understanding of columnar storage (Parquet), partitioning/clustering, distributed caching, and query engine optimization.