- ⚙️ Data Engineer skilled in building modular cloud-based ETL pipelines.
- 🔢 Academic background in Mathematics (BSc) & Data Science (MSc)
- 💼 Brief career in Management & Public Health Consulting
- 💻 Enjoys designing data architecture, and containerized workflows.
- Specialty: Using algorithms to design ETL packages/modules
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Modular & Maintainable Architecture: I design ETL pipelines as loosely coupled, reusable components to simplify debugging, enable parallel development, and support future scalability.
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Cloud-Native & Cost-Efficient: I leverage managed cloud services (e.g., AWS Glue, BigQuery, GCS, S3) and infrastructure-as-code to optimize for reliability, performance, and cost, while maintaining security best practices.
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Data Quality & Observability First: I embed validation, logging, and monitoring at each pipeline stage to ensure data integrity, enable fast issue detection, and support confident decision-making downstream.
- RegEx
- Apache Pulsar
- Go (for writing Kafka producers and multithreading)