Enterprise Data Engineer focused on data platforms, distributed systems, and enterprise-grade ingestion & processing pipelines.
My work sits at the intersection of system correctness, observability, and principled architecture — building systems that let teams reason about complex data flows, distributed behavior, and failure modes in a scientific, testable way.
- Distributed systems simulation, testing, and failure modeling
- Enterprise-scale data ingestion, validation, and transformation
- Correctness-oriented system design and validation layers
- Experimentation frameworks for data and backend systems
- Platform tooling that enables repeatable, inspectable system behavior
- Long-term system evolvability and architectural integrity
| Languages | Python, Java, JavaScript/TypeScript, SQL, C/C++ |
| Platforms | Azure, Spark, Docker |
| Domains | Data engineering, backend systems, platform tooling, simulation & testing infrastructure |