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Software Engineer @ Symplast
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Senior Software Engineer | Cloud-Native Backend | .NET | AWS | Distributed Systems
With over 8 years at DeÔnibus, I specialize in designing and evolving cloud-native distributed systems that power high-volume, revenue-critical platforms within a global, multi-brand travel environment. My work focuses on backend architecture, leveraging .NET and AWS to deliver robust solutions for checkout, payment processing, CMS, travel routing, and financial integrations, supporting both B2C and B2B channels. At DeÔnibus, I contribute to system architecture and scalability by leading decisions on service boundaries, data flow, and resilience. Using approaches such as Domain-Driven Design (DDD), CQRS, and event-driven patterns, I ensure high availability and fault tolerance across containerized workloads on AWS. My efforts align engineering solutions with business outcomes, enhancing performance, reliability, and growth in complex transactional systems. Based in Brazil (GMT-3)
Public LinkedIn data · Sep 15, 2026
In 2019 I led the rebuild of a shopping cart system that couldn't go down, not even for an hour, because it was the thing standing between browsing and paying. I had opinions about the new stack. Strong ones. But I didn't make a single one of the big calls alone. Every technology decision went through the team first. Not as a formality, as an actual filter. Twice, someone pushed back on a choice I'd already half-committed to in my head, and both times they were right. One of those pushbacks is the reason we don't have a piece of tech debt right now that I would've happily signed up for six months ago. The idea that actually saved us, though, wasn't a technology choice at all. It was splitting the whole rebuild into phases, and building each phase to work backward with what already existed. Old cart, new cart, running side by side, every step of the way. Nobody had to choose between "ship the new thing" and "keep checkout working." Both, always, at the same time. It's slower. It's also the only version of this project where a mistake in phase three doesn't take down what phases one and two already got right. What's a decision you made better by bringing in someone who disagreed with you?
Sim, estamos vendendo passagens de ônibus dentro do app da moovit 💪🤓 Com essa nova parceria, os usuários do Moovit encontrarão uma quarta aba na tela inicial do aplicativo, denominada “Bilhetes” . A partir dela, é possível selecionar origem, destino e dados de viagem, acessar múltiplas opções de rotas e adquirir bilhetes de diversas empresas de ônibus consolidadas em todo o Brasil, que são integrados ao DeÔnibus
Four years into this and I still got the order wrong on a mock interview last week. Question: a downstream service is flaky. Payment processor, doesn't matter which. What do you check first. I said retries. Wrong answer, and I've shipped enough AWS SQS consumers that I should've known better. Here's the order that actually holds up, in this sequence, not randomly: 1. Timeout. Fail fast. Skip this and every other fix just compounds the outage, because requests pile up behind an unbounded wait. 2. Retries, with exponential backoff and jitter. Not 3 retries in a tight loop. That's just you DDoSing your own dependency. 3. Circuit breaker. After N failures in a window, stop calling entirely and fail immediately. Give the service room to actually recover. 4. Fallback. Cached value, degraded response, queue it for later. Anything except a spinning loader. I had 3 and 4 flipped in my head for years. Fallback felt more "senior" to mention first, so I led with it. Backwards. If you fall back before you've stopped hammering a dying service, you're still adding load to something on fire. Curious how other people order this. Anyone here put circuit breaker before retries?
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Based on 36 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.
Based on 36 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.
Based on 36 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.
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Bruno Matuk Long is a B2B LinkedIn creator based in Brazil with 1,231 followers, posting about Software, Growth / GTM, and Sales. On Naano, one sponsored LinkedIn post by Bruno Matuk Long costs €332, a fixed price per post.
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