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Rodrigo BonattoRB
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Rodrigo Bonatto

@rodrigobonatto

Senior Software Engineer at PayPal building fault-tolerant payment services for fee calculation, ledger reconciliation, and fraud detection.

Brazil
Message

At PayPal, I work on scalability and reliability challenges in payment infrastructure. I implement Java, Kafka, and Kubernetes-based services for fee calculation and ledger reconciliation, with fault-tolerant, idempotent processing.

I also built fraud-detection pipelines and replaced manual matching with deterministic anomaly models. This work supports transactional integrity and financial correctness.

At Revelo, I orchestrated production systems with Terraform and Kubernetes, implementing Blue/Green deployments with graceful connection draining and readiness probes. I also architected a real-time event mesh using Kafka and gRPC in place of REST polling.

Across roles at CoinDesk, E-Core IT Solutions, Z3 Works, and Transamerica Retirement Solutions, I worked on Web3 platforms, distributed event-driven systems, IoT infrastructure, and Java Spring microservices. My research focuses on consensus protocols, fault tolerance, and algorithm design for consistency and availability.

Experience

Work history, roles, and key accomplishments

ES

Principal Software Engineer

E-Core IT Solutions

Feb 2020 - Jan 2022 (1 year 11 months)

Architected distributed event-driven systems and Go-based platforms, designing resilient serverless ingestion pipelines for millions of daily IoT telemetry events.

ZW

Full Stack Engineer

Z3 Works

Aug 2018 - Feb 2020 (1 year 6 months)

Architected serverless backend infrastructure for IoT ecosystems, integrating Node.js, DynamoDB, and Elasticsearch with connected devices for real-time synchronization.

Education

Degrees, certifications, and relevant coursework

Federal University of Santa Catarina logoFC

Federal University of Santa Catarina

Master of Science, Computer Science

Pursuing a Master of Science in Computer Science with research focus on consensus protocols, fault tolerance, and algorithm design for consistency and availability across failure modes and communication constraints. Expected graduation in March 2027.

University of Vale do Rio dos Sinos logoUS

University of Vale do Rio dos Sinos

Bachelor of Science, Information Systems

2016 - 2021

Completed a Bachelor of Science in Information Systems. Capstone involved research on deep learning-based computer vision for resource-constrained IoT environments, using the YOLO architecture to train and deploy real-time object detection models on edge devices.

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