AI-Native Data Platform Engineer

Denis IL

I build AI-native analytics systems — from scalable data platforms to autonomous AI agents.

View Work About Me

ClickHousedbtAirflowIcebergKafkaClaudeLangChainRAG

Professional Journey

Currently

True Gamers

Active

Data Analyst

Data collection & pipelines
Analytics & reporting
Automated reporting
Dashboard development
Data pipelines
Business intelligence

Career Evolution

Data Analyst

Where it started — SQL, metrics, dashboards, business context

→

Analytics Engineering

dbt · semantic layers · data modeling · governance

→

Data Platforms

DWH architecture · ClickHouse · Iceberg · Airflow

→

AI-Native Systems

LLM reasoning over data · autonomous agents · decision intelligence

About

Building data platforms for the AI era

Denis — AI-Native Data Platform Engineer. I design modern data foundations that turn trusted analytics into intelligent systems.

Open to projects

Data EngineeringAnalytics EngineeringAI-Native SystemsModern Data Platforms

What I Build

Data Platforms

Scalable DWH architecture with ClickHouse, PostgreSQL, and Apache Iceberg — built for both BI and AI workloads.

Analytics Systems

End-to-end pipelines from raw ingestion through dbt transformations to governed semantic layers.

AI Workflows

LangChain and Claude-powered agents that monitor KPIs, detect anomalies, and generate insights autonomously.

Decision Intelligence

Autonomous reporting systems where AI closes the feedback loop — from data to decision, no human required.

Engineering Philosophy

Reliable AI requires reliable data.

The principle behind every system Denis builds.

Data before AI

Modern AI is only as trustworthy as the data it reasons over. Foundations first.

From Dashboards to Decisions

The goal isn't a report. It's a decision made faster, with more confidence.

AI-Native Analytics

AI should operate on governed, structured, trustworthy platforms — not raw chaos.

Platform Thinking

Build once. Reuse at scale. Automate the feedback loop.

Tech Stack

The Stack

End-to-end data infrastructure — from ingestion pipelines to AI inference layers.

Data Engineering

PostgreSQLClickHouseAirflowDBTKafka

Lakehouse

S3Apache IcebergDuckDBParquet

Analytics

MetabasePower BI

AI / LLM

OpenAIClaudeLangChainRAG

Now

Current Focus

AI-native analytics

Semantic layers

Apache Iceberg

Autonomous analytics

AI agents over DWH

Featured Projects

Platforms built for real decisions

A selected preview of the engineering systems taking shape.

View All Projects

AI WorkflowFlagship

Active Dev

AI-Native Analytics Platform

A governed data platform designed for AI reasoning — Apache Iceberg lakehouse, dbt semantic layer, and a Claude-powered analyst that answers business questions with explainable, trusted metrics.

Apache IcebergdbtSemantic LayerClaudeS3

Data PlatformFlagship

Active Dev

Gaming Club Data Platform

End-to-end data infrastructure for gaming venue operations — automated ingestion pipelines, dbt transformations, and decision-ready analytics over a centralised PostgreSQL warehouse.

PostgreSQLClickHouseAirflowdbtMetabasePython

AI Workflow

Active Dev

AI Analytics Assistant

A governed conversational interface over ClickHouse. RAG-based context layer with LLM reasoning for natural language data exploration.

RAGLangChainClaudeClickHouse

Real-time

Concept

Tournament Intelligence

Real-time esports analytics platform. Kafka event stream, live stat aggregation, and AI-generated performance commentary.

KafkaPostgreSQLOpenAI

Analytics

Concept

Sports Analytics

Player performance modelling and fast ad-hoc exploration. DuckDB over Parquet files with Claude-assisted insight generation.

DuckDBParquetClaude

Telemetry

Research

ISS Analytics

Lakehouse experiment for orbital telemetry. Apache Iceberg on S3, Kafka ingestion, anomaly detection over time-series sensor data.

IcebergS3Kafka

Engineering Insights

Insights

Engineering articles on data platforms, AI analytics, and the architecture decisions behind trustworthy systems.

All Articles

2025-06-016 min read

Why AI Needs a Semantic Layer

LLMs can reason over data fluently. The problem is not capability — it is context. Without a semantic layer, AI analytics is a probabilistic exercise. With one, it becomes deterministic.

Semantic LayerAI Analyticsdbt

Read

2025-05-155 min read

Why Dashboards Fail

Most analytics investments produce dashboards. Most dashboards are underused within six months. The problem is not the tool. It is what dashboards are designed to answer.

AnalyticsDashboardsData Strategy

Read

2025-05-017 min read

Building Trustworthy Analytics

The most common analytics problem is not missing data. It is data nobody trusts. Trustworthiness is an architecture decision, not a QA process.

Data QualitydbtMetric Governance

Read

Architecture Patterns

Systems That Scale

Reusable architecture patterns — from traditional analytics stacks to AI-native platforms.

Architecture Library

AI-Native Analytics Platform

A governed data platform designed specifically for AI reasoning — semantic layer as the contract between data and AI.

Apache IcebergdbtSemantic Layer

SOURCE

Raw Data

Operational Systems · Event Streams

WAREHOUSE

Apache Iceberg

ACID · Schema Evolution · Time Travel

transform

DBT

dbt

Medallion Layers · Metric Contracts

govern

SEMANTIC

Semantic Layer

Business Context · Governed Metrics

reason

AI AGENT

AI Analyst

Claude · Explainable Answers

Medallion Architecture

The dbt-enforced three-layer data model that separates raw ingestion from transformation from business logic.

dbtRawStaging

SOURCE

Source Systems

Databases · APIs · Event Streams

WAREHOUSE

Raw Layer

Insert-only · Full history

clean

DBT

Staging Layer

Typed · Deduplicated

model

SEMANTIC

Mart Layer

Business logic · Governed metrics

serve

REPORTING

Consumers

BI tools · AI agents

Contact

Let's build something.

Open to AI-native data projects, consulting, and engineering conversations.

Get in Touch LinkedIn