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Data Systems Rust Developers in Poland

Developed resilient backend systems using Rust and Elixir for cloud environments. Designed microservices architectures to enhance scalability and maintainability. Implemented data-intensive applications with advanced SQL optimizations.

• Developed resilient cloud backend systems
• Designed microservices architectures
• Implemented data-intensive applications

Built backend services in Rust and Erlang for distributed systems. Developed concurrent data processing pipelines and optimized SQL queries for robust data handling.

• Architected scalable microservices with Java
• Enhanced system reliability using Python for testing
• Integrated cross-platform solutions using C

Built a Rust complex-event-processing engine that composes reusable processing blocks into Kafka-consuming and Kafka-producing deployments. The system uses Tokio tasks, NATS stage transport, embedded Python execution, and dependency-aware input routing to reproduce production-grade stream-processing architecture.

• Implemented bidirectional PyO3 type marshalling across the FFI boundary
• Managed Python GIL boundaries for in-process block execution
• Developed Linux filesystem drivers and embedded firmware
• Built distributed event-driven backends in Scala, Java, and Go

Engineered quantitative models using Rust and Python for financial analytics. Managed cloud-based data processing on AWS and Azure, optimizing cost and efficiency.

• Developed API integrations for trading platforms
• Utilized Google Cloud for scalable data storage
• Created dashboards for real-time financial metrics

Engineered cross-platform software systems with Rust and Go for distributed environments. Optimized x86 assembler code for performance-critical applications. Developed real-time data processing solutions for cloud services.

• Engineered cross-platform systems with Rust and Go
• Optimized x86 assembler for performance
• Developed real-time data processing solutions

Built cloud data platforms and migration architectures, including an on-premises SQL Server warehouse transition to Azure Synapse and SAP S/4 extraction pipelines. Works across infrastructure automation, observability, performance engineering, security compliance, and cost optimization for data-intensive systems.

• Terraform-based Azure infrastructure provisioning
• Polars and Dremio analytical data processing
• Splunk observability for production platforms
• SAP extraction tooling compliant with SAP Note 3255746

Architects Rust async services for low-latency market-data ingestion, normalization, pricing, and execution across multiple trading venues. Previously operated an IoT platform processing thousands of telemetry events per second from hundreds of thousands of field machines during migration to AWS serverless event processing.

• WebSocket reconnection and gap recovery
• Lock-free state sharing with ArcSwap
• Single-writer and sequencer patterns
• Market microstructure modeling

Engineered scalable backend systems using Go and Rust, focusing on high-availability and fault-tolerant architectures. Developed data-intensive applications with a strong emphasis on performance and reliability.

• Led the migration to a microservices architecture in Go
• Optimized query performance in Postgres for large datasets
• Implemented CI/CD pipelines for automated testing and deployment

Led development of distributed systems using Rust and Scala for high-performance computing. Applied TypeScript for robust front-end interfaces.

• Implemented machine learning pipelines in Python
• Designed Kotlin-based microservices for cloud platforms
• Authored Java libraries for data processing

Engineered a distributed messaging system handling millions of transactions per second. Specialized in building high-performance, low-latency backend services for financial applications.

• Contributed to the development of a consensus protocol
• Optimized C++ code for a high-frequency trading platform
• Led the migration of monolithic systems to microservices architecture

Led the design and deployment of scalable backend systems using Rust and Kafka for real-time data processing. Expert in building microservices architecture with a focus on high availability and resilience.

• Integrated Go and Python for cross-service communication
• Implemented C# modules for legacy system support
• Utilized SQL for complex data transformations

Architected cloud-native platforms using Rust and Python for high-frequency trading. Integrated Solana blockchain with gRPC for secure transaction processing.

• Optimized Nautilus Trader for low-latency execution
• Developed microservices with container orchestration
• Implemented real-time data analytics pipelines

Led architecture of large-scale systems using Rust and Python. Developed high-frequency trading platforms with C and C++ for financial markets.

• Implemented machine learning models with Java
• Optimized web applications with JavaScript
• Designed scalable infrastructure solutions

Engineered distributed systems with Scala and Rust, focusing on fault tolerance and scalability. Applied functional programming techniques to simplify complex algorithms.

• Designed domain-driven architectures
• Optimized Python applications for performance
• Developed real-time data streaming solutions