Mid-Level Observability Engineer
EBANX - São Paulo or Curitiba
Posted Mar 27, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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Where they hire
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About this role
Mid-Level Observability Engineer São Paulo or Curitiba EBANX is one of the most successful fintechs to emerge from Latin America, and today we are building a truly global payments company. Our mission has remained the same since day one: to expand access and enable companies and consumers to participate in the digital economy, no matter where they are. What started as a bold vision has evolved into a platform that connects some of the world's largest digital companies with customers across 21 of the fastest-growing markets. We operate where complexity exists transforming local challenges into global opportunities and building the infrastructure that allows payments to move further, faster, and smarter. We are a team of builders and problem solvers. We think globally, act with curiosity, and believe that diversity of thought is a competitive advantage. As EBANX enters its next phase of hypergrowth, we are looking for people who want to shape the future of payments, expand what's possible, and help connect businesses and consumers across borders. Let's build what's next together. What your day-to-day will look like - Develop, enhance, and maintain observability solutions using Splunk , ensuring end-to-end visibility of payment flows; - Build, refine, and optimize dashboards, searches, and correlations for proactive detection of anomalies and performance degradation; - Define and evolve alerts and monitoring indicators, reducing false positives and increasing monitoring accuracy; - Analyze logs, metrics, and events to identify root causes and support incident response; - Work on data ingestion, structuring, and standardization (logs and
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