Vasoli
Go, Kafka, and PostgreSQL ETL pipeline for financial transaction workflows.
V
Vasoli
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Architecture flow
4 layersProblem
Financial transaction systems need reliable ingestion, transformation, and storage without losing security or fault tolerance.
My Role
Built backend pipeline components across API design, streaming, transformation, and persistence concerns.
Solution
Go services expose secured API endpoints, stream transaction events through Kafka, transform payloads, and persist structured records in PostgreSQL.
Stack
Case study
Problem
Financial transaction systems need reliable ingestion, transformation, and storage without losing security or fault tolerance.
Proof signal
Go services · Kafka streaming · PostgreSQL · JWT-secured APIs
My Role
Built backend pipeline components across API design, streaming, transformation, and persistence concerns.
Core product work
- Event ingestion
- ETL workers
- JWT-secured APIs
Solution
Go services expose secured API endpoints, stream transaction events through Kafka, transform payloads, and persist structured records in PostgreSQL.
Go services expose JWT-secured API endpoints, stream transaction events through Kafka, transform payloads through ETL workers, and persist structured records in PostgreSQL.
Architecture Highlights
JWT-secured REST ingestion endpoints
Kafka-backed event streaming
PostgreSQL persistence for structured transaction data
Challenges and Tradeoffs
- Keeping transaction payload flow reliable across service boundaries.
- Designing secure ingestion without adding unnecessary complexity.
Impact / Outcome
- Built a backend-heavy prototype for financial data ingestion and transformation.
- Practiced fault-tolerant pipeline design around event streaming and persistence.
Learnings
- Streaming pipelines need simple contracts between producers, workers, and storage.
- Backend reliability starts with clear payload validation and failure handling.
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