Data & AI Solution Architect
Databricks · Lakehouse Engineering · Data Modeling · Platform Architecture
I have worked with data since 2011, from BI and ETL to distributed processing, Machine Learning, and Data & AI architecture. My current focus is building reliable, governed data platforms with Databricks.
Explore my work · Browse my knowledge map · LinkedIn
Since October 2025, I have been working on the construction and evolution of a data lakehouse, leading the implementation of engineering best practices and code refactoring while incorporating new data use cases.
My main contributions focus on two areas:
- Shared data processing framework: replaced manually triggered, table-specific jobs and notebooks with common data loading logic, extending the approach to Bronze-to-Silver processing where transformations allowed it.
- Hub-and-spoke architecture: redefining the lakehouse to reuse shared data across projects, reduce duplication from separate project schemas, and support the addition of new use cases.
How I approach compute selection, environment isolation, platform trade-offs, and dimensional modeling.
Read a compute decision · Browse architecture notes
My 2019 academic proof of concept connects financial-news ingestion, Kafka, distributed storage, and operational monitoring. The repository preserves the thesis and a proposed continuation for 2026.
This GitHub also holds my learning notes, experiments, reading, and personal reflections. Some pages are reviewed references; others are drafts or historical material. Their status belongs alongside the content.
Technical and personal knowledge map · Life beyond technology
Principles I return to
- Be a good person.
- Know something about everything, and everything about something.
- 80/20.
- Think big, start small.
- Stoicism.
- Feminism.