Website: landerox.com | LinkedIn | Hugging Face
I build data and AI systems that are reliable, scalable, and practical to run.
From legacy IBM iSeries/AS400 to modern warehouse/lakehouse stacks, I have spent 15+ years building and improving data platforms. These days my focus is data architecture, data engineering, and production AI across Google Cloud, equivalent stacks on other cloud platforms, and open source solutions.
- Data pipelines: ETL/ELT, event-driven systems, and streaming + batch processing.
- Modern data platforms: Warehouse/lakehouse architectures that teams can actually operate.
- Cloud foundations: IaC, CI/CD, and delivery workflows that keep projects moving.
- Applied AI: RAG pipelines, LLM integrations, and evaluation workflows.
- Platform cleanup: Technical debt reduction, reliability hardening, and cost optimization.
- Patterns: Event-driven, Medallion, and Lambda/Kappa where they fit.
- Reliability first: Data contracts, schema evolution, idempotency, deduplication, quality gates, and replayability.
- Table strategy: Apache Iceberg first, plus BigQuery native and Delta/Hudi interoperability when needed.
- Engineering standards: Pre-commit, IaC-first, SemVer, and Conventional Commits.
Cloud Platforms (GCP Focused)
Data & Analytics
AI & ML
Compute & Messaging
Orchestration
DevOps & Infrastructure (IaC)
Data Engineering & Orchestration
Production AI & Applied MLOps
Languages, Libraries & Formats
Databases

