Backend engineer · Payment infrastructure · Berlin
Three years building high-throughput payment infrastructure in Go and Kafka — including a 40% cut in payment processing latency at Stripe.
Case study
How he redesigned Stripe's payment event fan-out service to cut end-to-end latency.
The payment event fan-out service relied on synchronous HTTP calls.
Redesigned the service in Go, replacing the synchronous HTTP calls with Kafka-based async messaging.
End-to-end processing latency reduced by 40%.
Services & infrastructure
Payment and payroll systems built at Stripe in Berlin and Buk in Santiago.
Built idempotent retry logic for charge reconciliation, covering three merchant tiers.
99.7% of duplicate-charge incidents eliminated
Structured traces, metrics and logs added to the payment services via OpenTelemetry.
MTTR on payment service alerts from 28 min to 9 min
Contributed to a service template that standardises health-check and graceful shutdown patterns.
Adopted by 6 other backend teams
REST APIs for a payroll calculation engine, written in Go with PostgreSQL.
Serving 1,200 Chilean SME clients
Legacy batch payroll jobs migrated to event-driven workers.
Monthly processing from 6 hours to 35 minutes
Integration and contract tests written over 8 months.
Service coverage raised from 54% to 88%
Tech stack
A backend engineer specialising in distributed systems and event-driven architecture, with a strong focus on reliability, observability and clean API design.
Diego is a Backend Software Engineer at Stripe in Berlin, working on high-throughput payment infrastructure in Go and Kafka. Before that he was a Junior Backend Developer at Buk in Santiago, building payroll APIs and event-driven workers, and interned at Cornershop (Uber).
At Buk he was part of the on-call rotation and resolved 12 production incidents, each with a documented postmortem.
Experience
Stripe, Berlin
Payment event fan-out redesign (40% lower latency), idempotent charge-reconciliation retries, OpenTelemetry observability and the internal Go service template.
Buk, Santiago
Payroll calculation APIs for 1,200 SME clients, event-driven payroll workers, test coverage from 54% to 88%; on-call with 12 incidents resolved.
Cornershop (Uber), Santiago
Built a data pipeline aggregating delivery-time metrics from Kafka topics into a PostgreSQL reporting schema; shipped two bug fixes to the order-status microservice, both merged and deployed.
Education & certifications
Contact
diego.reyes@email.com
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