Architecture article · 2 min · short read
Designing Medallion Architectures for Production
Bronze, Silver and Gold are useful when each layer owns a responsibility. When data is copied only to satisfy the diagram, the pattern stops helping us think.
AI-Native Principal Engineer · Data Platform Architect · Databricks Specialist
Built on experience. Driven by what’s possible.
Designing and building data platforms, software and AI systems with deep engineering foundations and an AI-native way of working.
root@15x1976
Architecture & Engineering
Data Architecture, Databricks, and Data Engineering applied to designing, building, and evolving production Data Platforms.
Technical article · 1 min · short read
Engineering Databricks Asset Bundles for Production
As a data platform grows, jobs, configuration and deployment deserve software discipline too. Asset Bundles are one mechanism for that discipline, not the thesis itself.
Technical article · 3 min · short read
Designing Metadata-Driven Data Platforms
An SAP ingestion platform grew by creating a pipeline for every new table. The alternative was changing the unit of growth from tables and pipelines to reusable extraction patterns.
Architecture article · 1 min · short read
Data Governance as a Platform Architecture Capability
Access control is security. Governance goes further: what does the data mean, who owns that meaning, and under what conditions can it be trusted?
Technical article · 2 min · short read
Designing Data Orchestration with ADF and Databricks Workflows
ADF and Databricks Workflows overlap, but choosing a universal winner is less useful than deciding where each responsibility starts and ends.
Technical article · 1 min · short read
Designing Idempotent Data Pipelines
A pipeline that works once is not necessarily finished. The real design shows up when the same unit of work must be executed again without corrupting state.
Technical article · 2 min · short read
Engineering Data Pipelines for Schema Evolution
Sources change even when our pipelines do not. Good boundaries make schema, data and semantic drift observable before they become silently wrong data.
Technical article · 1 min · short read
Physical Data Design and Performance in Databricks
A table can contain the right data and still perform badly. How those bytes are physically distributed can matter as much as the transformation that produced them.
Technical article · 1 min · short read
Data Reliability and Recovery with Delta Lake Time Travel
Time Travel feels optional until the first bad overwrite. Then it becomes a powerful recovery tool—while still not being an infinite backup.
Technical article · 1 min · short read
Designing Incremental Data Pipelines with Change Data Capture
Reading everything again can be the right strategy. It becomes questionable when we know what changed and still pay to ignore that information.
Technical article · 1 min · short read
Data Lineage as a Core Platform Capability
Without lineage, every important change becomes detective work: who produces this table, who consumes it, and what breaks if we change it?
Architecture article · 4 min · short read
Modernizing Data Architecture from Warehouse to Lakehouse
Moving from a Data Warehouse to a Lake does not automatically remove old constraints. If we copy every old decision without revisiting its purpose, we only relocate them.
Technical article · 3 min · short read
Designing Reusable Data Platform Capabilities
Industrializing a data factory means turning repeated decisions into reusable capabilities and reserving engineering for what is genuinely new.
Technical article · 1 min · short read
The Notebook Is Not the Application
A notebook can be an excellent interface without also owning configuration, secrets, business logic, orchestration and recovery.
AI-Native Engineering
AI applied to the Data Platform, the engineering process, and the way augmented teams are built.
Library · technical essay · 21 min · deep read
Human and Machine: An Architecture for Thinking and Building Together
A working architecture for combining human judgment and artificial intelligence without losing context, accountability, or continuity.
Library · technical essay · 17 min · deep read
The Cognitive Cell: AI-Augmented Teams
A model for turning individual AI productivity into collective capability by coordinating context, specialties, and decisions across a team.
ABOUT
20+ years of engineering. Pushing the limits of what we can build.
Experience across software, data and architecture applied to a way of working that combines technical judgment, hands-on building and AI.
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