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Data Systems Rust Developers

Engineered high-performance data processing pipelines using Scala and Rust, focusing on real-time analytics. Designed and maintained distributed systems for large-scale data ingestion and processing.

• Built microservices architecture using Go and Java
• Integrated TypeScript for front-end data visualization
• Optimized C++ algorithms for data compression

Designed MLS group-state features and bidirectional streaming transport for secure messaging, including ordered delivery, heartbeats, reconnects, external invites, and per-field permissions. Reduced 100-device group-invite storage from 8 MB to 200 KB and reduced full-group database loading from 13 reads to one.

• Migrated core product infrastructure into Rust
• Built FFI boundaries for untrusted drivers
• Enabled PostgreSQL through asynchronous database traits
• Shipped four protocol improvement proposals

Builds high-throughput, low-latency distributed systems for real-time trading, regulated payments, and firehose-scale data ingestion using functional Scala and concurrent streaming architectures. Has modernized legacy JVM platforms into independently deployable services and operated production workloads across public-cloud Kubernetes environments.

• Akka-to-Pekko zero-downtime migration
• Kafka and Kinesis event pipelines
• Cats-Effect, FS2, and ZIO
• PostgreSQL service backends

Designs distributed event-streaming and data-platform systems for payments and personalized media, including Kafka and ClickHouse pipelines processing billions of records. Production work spans Scala, Java, Kotlin, and Rust services with migrations across messaging, storage, and service architectures.

• Implemented event-sourced and CQRS service architectures
• Used Kafka, gRPC, and Protobuf for interservice transport
• Deployed workloads through Kubernetes and Argo CD
• Instrumented systems with Prometheus, Grafana, and Jaeger

Designed a Kafka-fed Rust caching service for a sanctions platform whose nightly database workload reached approximately 21 billion requests. The architecture reduced that traffic to fewer than four million requests while supporting migration from legacy sanctions workflows into a PostgreSQL-backed platform.

• Built real-time backend services with Python and Node.js
• Developed React interfaces for sanctions operations
• Modernized end-of-life application workflows
• Eliminated recurring manual database updates

Designed a stable ABI for cross-language Rust interoperability, including an intermediate representation, generated type conversions, validity checks, opaque types, generics, custom DSTs, and runtime tagged dispatch. Added WebAssembly smart-contract execution to Hyperledger Iroha and corrected consensus, fault-handling, and peer-synchronization defects.

• Unsafe Rust and memory-layout engineering
• Procedural macro and code-generation tooling
• cbindgen associated-type resolution
• Concurrent Java ETL and stream replication

Developed quantitative trading systems using Rust and C++, focusing on high-frequency trading algorithms. Implemented smart contracts for decentralized finance applications.

• Built high-frequency trading algorithms
• Developed DeFi smart contracts
• Specialized in quantitative finance systems

Designed and owned low-latency execution, market-data, simulation, and quantitative research infrastructure for multi-asset trading. Applied Rust and C++20 performance engineering across NUMA-aware optimization, lock-free queues, CPU affinity, IRQ tuning, binary feeds, FIX, and lossless gigabit packet capture.

• CEX, DEX, and DeFi trading systems
• MiFID II and PCI DSS exchange architecture
• perf, VTune, and flame-graph profiling
• Memory-cache and scheduler optimization

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

Architected scalable database systems using Rust, focusing on high availability and fault tolerance. Led the design of business applications with a strong emphasis on technical specifications.

• Developed distributed database engines from the ground up
• Designed architecture for large-scale data warehousing
• Optimized query execution plans for performance gains

Builds backend systems, desktop software, API integrations, and AI automation workflows across Rust, Python, and native C++. Recent work includes payment reconciliation, operational platforms, distributed services, and document-context retrieval pipelines.

• Maintains PostgreSQL, MySQL, DynamoDB, and SQLite systems
• Deploys infrastructure with Kubernetes and Terraform
• Implements REST APIs and webhook integrations
• Builds LLM agents with n8n and Make

Developed asynchronous Rust and Tokio services for Solana MEV trading, including arbitrage, liquidation, Jito submission, and bundle lifecycle tracking. Also isolated transaction signing and key-generation workflows behind a dedicated Rust API for custody-sensitive operations.

• Built matching and pre-trade risk components
• Used ClickHouse for market-data workloads
• Implemented Kafka and NATS messaging
• Profiled p95 and p99 latency

Led development of distributed systems using Rust and Go, emphasizing consistency and availability. Architected scalable microservices with TypeScript for cloud environments.

• Implemented serverless functions with Python
• Developed frontend frameworks with JavaScript
• Optimized database performance

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