DENIS IL.
AI-Native Data Platform Engineer

Denis IL

I design and build data foundations that turn trusted analytics into intelligent, autonomous systems.

Open to projects
Professional Background

Started as a data analyst — learning what real business questions look like when they arrive as a Slack message at 9am. One thing became obvious quickly: analysis is rarely the bottleneck. The data infrastructure underneath almost always is. I began rebuilding it — writing the pipelines, modeling the logic, automating the reports. The shift from analyst to platform engineer wasn't planned. It was the natural answer to a problem that kept repeating.

Currently

True Gamers

Active

Data Analyst

Focus Areas
Analytics
Data Engineering
Automation
Business Intelligence
Career Evolution
01

Data Analyst

SQL · metrics · dashboards · business context

02

Analytics Engineering

dbt · semantic layers · data modeling · governance

03

Data Platforms

DWH architecture · ClickHouse · Iceberg · Airflow

AI-Native Systems

LLM reasoning · autonomous agents · decision intelligence

Engineering Philosophy

Reliable analytics starts with reliable data.

Every AI system is only as trustworthy as the data foundations beneath it.

Automation scales decision making.

The goal isn't reporting. It's removing the human from the feedback loop entirely.

AI requires trustworthy data foundations.

LLMs don't fix bad data. They amplify it. Build the foundation first.

Currently Learning

Deepening expertise in the next layer of the stack:

Apache Iceberg
Lakehouse Architecture
Semantic Layers
Autonomous Analytics
AI Agents
Vision

Building the data stack
for AI-native intelligence.

The next generation of analytics systems won't just visualise data — they'll reason over it, act on it, and close the feedback loop autonomously. I'm building toward that future: AI-native systems that combine governed data platforms, semantic layers, and autonomous AI agents into a single, coherent stack.

Get in Touch