Modern Data Stack Engineering
Comprehensive coverage of building, optimizing, and scaling modern data architectures using cloud-native tools like Databricks, Snowflake, and dbt.
The articles and projects here focus on practical implementation—medallion architecture patterns, cost optimization, pipeline design, and choosing between platforms like Databricks and Snowflake. If you're building or evolving a data platform, this is where to start.
Articles
Six Months with Cursor on Databricks — Why Did I Wait on Skills?
field note · · Updated
After half a year of AI-assisted Databricks work in Cursor, installing official Databricks agent skills changed more than any model swap. Here is what was missing — and why I should have done it on day one.
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Databricks Cost Optimization: 5 Commands You Run Directly from Cursor
tutorial · · Updated
Five practical tips for optimizing Databricks costs that you can run directly from Cursor. From finding unused clusters to analyzing Spark configurations and reducing data spill.
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Code Insights — Local Coding Analytics for AI Developers Without Cloud Tracking
tutorial ·
How I implemented and am testing Code Insights — a privacy-first CLI tool that tracks my coding patterns locally in SQLite, without API keys and without data leaving my machine.
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How I Cut My AI Agent Development Costs by 90% with OpenRouter and Cursor
tutorial ·
A practical breakdown of how I route AI model traffic through OpenRouter to keep Cursor coding costs near zero — including the weekly email workflow that keeps my model roster current.
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Beyond the Spin: Building a Creative Loading Bar in Streamlit for Better UX
case study ·
When Databricks queries take 5–20 seconds, a static orange banner feels like an error. Swap in a branded Automower animation with the same Streamlit context-manager API.
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LINHAC 2026 — Conference Report
field note ·
LINHAC 2026 confirmed a clear shift: hockey analytics is becoming core infrastructure, not a side project. This report summarizes the strongest research signals, practical club examples, and what organizations should prioritize next.
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When to Use a Consultant Instead of Hiring: A Data Engineering Perspective
analysis · · Updated
Hiring a senior data engineer costs €120–200k the first year. But for bounded projects — Databricks buildouts, dbt migrations, lakehouse design — consulting delivers faster and cheaper. Here is when each makes sense.
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22 Articles in 26 Days: Session Data, Keywords, and What the Automation Actually Produces
case study · · Updated
Four weeks of build in public: 22 n8n tutorials published, 951 sessions, 38 ranked keywords, and 2 top-10 rankings — without a single external backlink. Here are the numbers, without spin.
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n8n Split in Batches Node: Processing Large Datasets Without Hitting Rate Limits
tutorial · · Updated
When you need to process thousands of records in n8n, feeding them all at once into an API or database crashes the workflow or triggers rate limits. The Split in Batches node is how you process large datasets reliably — here is how it actually works.
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Agentic Data Organisation: How I Set Up an AI-Driven Data Organisation with Claude
case study · · Updated
A practical walkthrough of my agentic data organisation: roles, ownership, agent coordination, and how Claude drives decision flow across analytics, platform, and governance.
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n8n Merge Node Modes Explained: Combine, Multiplex, and Pass-Through Under Partial Input
tutorial · · Updated
The n8n Merge node has four modes with subtle behavior differences that only surface with partial input, mismatched item counts, or timing gaps between branches. Here is what each mode actually does.
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n8n Error Trigger: Workflow-Level Error Catching and When It Actually Fires
tutorial · · Updated
The n8n Error Trigger node is a workflow that runs when another workflow fails — but the when and why are full of edge cases. Here is how it actually works, what it misses, and how to build reliable error handling in production n8n.
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From Raw Data to Revenue Decisions: Building an End-to-End Analytics Platform
case study ·
How I designed and shipped a full-stack data intelligence system for a global manufacturing company — from Databricks pipelines to AI-powered dashboards.
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Master n8n: Building Robust Data Pipelines with Workflow Automation – A Step-by-Step Guide
article · · Updated
Learn how to build powerful and robust data pipelines using n8n. Step-by-step setup, practical examples, and patterns for reliable automation.
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From BI Reporting to Data-Driven Automation: A 10-Year Evolution of Data Strategy
analysis ·
How data strategy evolved from static BI reports to AI-powered automation. Learn from 10 years of data engineering experience: from centralized reporting to data mesh, and why making AI investments pay for themselves requires collapsing legacy and modern stacks.
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n8n vs Zapier vs Make.com vs sim.ai: Which Workflow Automation Tool is Best in 2025?
article ·
Comprehensive comparison of the top workflow automation platforms: n8n, Zapier, Make.com, and sim.ai. Find the perfect tool for your automation needs with real-world examples, pricing analysis, and expert recommendations from a data engineer.
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Beyond Dashboards: How to Build Living Data Experiences with Conversational Analytics
analysis ·
Dashboards fail because they require users to go somewhere else. Data prototyping expertise: learn how proactive insights and conversational analytics replace traditional dashboards with living data experiences.
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Integrating APIs with n8n: A Simplified Approach to Workflow Automation
tutorial ·
As an agentic engineer, I've worked on numerous projects that involve integrating multiple APIs to create seamless workflows. ...
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Projects
Enterprise ML & Data Platform — 100 Jobs, 631 Tables, NLP at Scale
production
End-to-end data and ML platform for a global manufacturing company. 100 Databricks jobs, 631 Unity Catalog tables, support intelligence across 1.46M cases, production churn models, demand forecasting, and a 17-page Streamlit dashboard — built and operated solo over three years.
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End-to-End Analytics Platform — Databricks, Streamlit & GPT-4o
production
Full-stack data intelligence system for a global manufacturer. Medallion architecture on Databricks, AI-powered natural language querying, z-score anomaly detection, and 10 production dashboards covering 14 markets — shipped in 12 weeks.
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Conversational Analytics Prototype - Beyond Dashboards
prototype
Interactive prototype demonstrating the future of data analytics: natural language queries, proactive insights, and zero-training data exploration. Built to show what comes after traditional dashboards.
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MCP-Connected Development Workflow for Data-Informed Prototyping
prototype
Connected Claude to analytics, research, strategy, and design context through MCP to build React prototypes inside the development environment.
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From SLA Reporting to Proactive IT Operations
historical
A Power BI and SQL analytics layer for finding patterns in ServiceNow data and turning SLA reporting into operational improvement.
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Food-Waste Marketplace MVP with Django
historical
An early full-stack marketplace connecting consumers with surplus food from local restaurants and grocery stores, built as a focused Django and Bootstrap MVP.
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All Topics
Modern Data Stack Engineering
Build and optimize modern data architectures with cloud-native tools.
Workflow Automation & Orchestration
n8n orchestration, API automation, and where workflows fit under agents.
Hockey Analytics & Sports Data Science
AI-powered hockey analytics and advanced sports data science.
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Modern web development with Astro, TypeScript, and performance optimization.
Developer Productivity & Tooling
Developer workflows, tooling, and productivity patterns for technical professionals.
Stockholm/Nordic Data Engineering Market
Stockholm tech scene, Nordic data engineering market, and local insights.
Conversational Analytics & Next-Gen BI
Conversational analytics, natural language interfaces, and next-gen BI.
AI Agents, Company OS & Agentic Systems
Cost/ROI routing, agent organizations, Company OS, MCP.