From complex data to enterprise-scale AI
I help teams and companies turn complex data — structured and unstructured alike — into AI they can actually use: from hands-on prompting workshops and Python automation to enterprise platforms that parse and embed documents and expose them to AI agents over MCP.
How your data becomes usable AI
Your data
Parse & embed
AI you can use
5+ yrs
Senior data engineer & technical lead, now an independent Cloud & AI consultant.
Core stack & platforms
- Microsoft Azure
- Databricks
- Palantir Foundry
- Azure Data Factory
- Apache Spark
- PySpark
- Delta Lake
- Unity Catalog
- Databricks Workflows
- Azure DevOps (CI/CD)
- Python
- SQL
- Scala
- Bash
- Git
- Large Language Models
- AI Agents
- Model Context Protocol (MCP)
- Unstructured Data & Embeddings
Services
From your first AI workshop to enterprise-scale data platforms
AI Starter — Prompting Workshops
Hands-on workshops that teach your team to write effective AI prompts and build simple AI solutions themselves — no technical background needed.
- Practical, jargon-free sessions
- Ready-to-use prompt templates for your industry
- Intro call + practical small-team format
- Materials and next steps you can reuse
- Clear scope before we start
Python Automation Mini-Consultations
Short, intensive sessions that simplify repetitive business processes — with code, documentation, or an implementation plan depending on scope.
- Live-coding on your real data & processes
- Code review & refactoring of existing scripts
- Report automation & system integrations
- Working scripts, docs, or an action plan
- Designed to reduce repetitive manual work
1:1 Technical Coaching & Developer Enablement
Personalized mentorship for data engineers and developers — master the modern data stack and integrate AI into your daily workflow.
- Modern data stack (Spark, Databricks, Azure)
- Unblock complex architectural problems
- Practical AI/API integration
- 1-on-1, tailored to your goals
Enterprise AI Integration & Workflows
Strategically embed AI into your operations — scalable, AI-driven workflows connecting enterprise systems with AI agents via Model Context Protocol (MCP).
- AI workflow design
- AI agents via MCP
- Process automation
- Integration with existing systems
AI Readiness Audits & System Analysis
A deep-dive technical review of your data platform — performance, bottlenecks, and how ready your infrastructure is for AI, with actionable recommendations.
- Architecture & performance review
- Bottleneck identification
- AI-readiness assessment
- Cost optimization & scalability roadmap
Data Strategy & Pipeline Architecture
Robust, secure data lakes and pipelines that form the foundation for enterprise AI.
- Secure Azure data-lake design
- Structured & unstructured data
- Scalable Delta Lake pipelines
- Complex source integration (ERP, CRM, APIs)
How I work
Practical, hands-on, and built to leave you self-sufficient
① Before
Free discovery call
We start with a short, no-cost call to understand your goals, processes, and data — so the work targets what actually matters.
② During
Hands-on live sessions
We work live on your real processes and data. I teach as we go — I don't just do it for you, so your team stays self-sufficient.
③ After
You keep everything
You keep the deliverables — working code, docs, or a clear action plan — with clear next steps for implementation.
Focus areas
Where I go deep
Azure Cloud Architecture
Secure, cost-efficient Azure cloud architectures and end-to-end data platforms.
Data Engineering & Platforms
Scalable Databricks/Spark pipelines, Unity Catalog, Delta Lake — enterprise-grade data lakes built to last.
Enterprise AI & LLMs
Practical AI integration: LLMs, AI agents, and unstructured-data pipelines via MCP.
Case studies
Selected results from recent work
~40% lower compute costs
Migrated data pipelines from Azure Data Factory all-purpose compute to Databricks Workflows (job clusters) and established CI/CD — cutting compute costs by ~40%.
Company-wide Data Lake
Helped to build a company-wide Data Lake on Palantir Foundry, integrating new sources for deeper, more granular insight.
Unstructured data → AI agents
Architecting a company-wide unstructured-data repository — parsing and embedding structured and unstructured data and feeding it to AI agents via MCP.
About
Kajetan GęgotekI’m Kajetan Gęgotek — a senior data engineer and technical lead and independent Cloud & AI consultant. With over five years of experience, I’ve gone from helping build a company-wide data lake on Palantir Foundry to owning the architecture and key technical decisions for a ~10-person Data Lake team — designing secure Azure environments, driving migrations (Hive Metastore → Unity Catalog), and pioneering unstructured-data + AI-agent infrastructure. Through KG Consulting I bring that enterprise experience to teams and companies of every size — from a first AI prompting workshop to enterprise-scale AI integration.
Certifications
- Databricks Certified Data Engineer Associate (2024)
- Databricks Certified Associate Developer for Apache Spark 3.0 (2022)
- Microsoft Certified: Azure Data Fundamentals (2021)
- AWS Certified Cloud Practitioner (2021)
Let’s talk
Tell me where your data or AI is stuck — I’ll tell you what’s worth doing first.
[email protected] · LinkedIn · Poland · Remote