I'm Jalalledin "Moji" Taavoni — a Data Engineer (Azure data platform · SQL Server · BI) who also takes AI to production, based in Milano 🇮🇹.
I build the unglamorous machinery that makes data trustworthy: metadata-driven ETL, star-schema datamarts, incremental loads that survive 2 a.m., and the CI/CD + governance around them. Then I bring AI to production the same way — from notebook demo to a system that runs reliably, observably, and at the right cost.
const moji = {
role: ["Data Engineer", "DataOps / Data Platform", "AI Integration (production)"],
stack: ["SQL Server", "Azure Data Factory", "Synapse", "Fabric", "SSIS", "SSAS",
"Power BI", "Databricks", "dbt", "Neo4j", "Python", "Azure", "LangChain"],
philosophy: "Thoughtful before fancy.",
education: "Computer Science + Digital Humanities · Università di Pisa",
currently: "Metadata-driven datamarts on Azure — and taking AI to production",
open_to: "Freelance & contract · IT and Remote EU",
reach: ["mojitmj.github.io", "linkedin.com/in/mojitmj", "t.me/mojitmj"],
};☁️ Cloud · Platform · DevOps
💾 Data Engineering · DataOps
🧠 AI · ML · LLMs (the growth edge)
💻 Languages · Tools
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PowerShell tool that x-rays a SQL Server / Azure SQL instance in one command — full DDL, DMVs, backup history, security audit, design-quality checks, per-table data samples. Cross-platform schedulers (Task Scheduler · SQL Agent · SSIS · cron · systemd).
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Metadata-driven Azure Data Factory ingestion template — managed-identity auth, multi-env CI/CD (dev/staging/prod), and PR validation (JSON schema + hardcoded-secret scanning). Drop-in for any ADF estate.
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Digital-humanities side project: 175 years of Italian academies as a property graph in Neo4j, visualized in the browser with popoto.js. Where data engineering meets the archive.
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Live portfolio: dual-positioning landing page (AI / DataOps / DE / BI / DA), animated streaming-source boot, EN/IT toggle with Italian-flag theme, live chat overlay, full visitor metadata pipeline.
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From: 09 June 2026 - To: 16 June 2026
Total Time: 27 hrs 54 mins
Markdown 12 hrs ████████▓░░░░░░░░░░░░░░░░ 35.13 %
Python 5 hrs 28 mins ████░░░░░░░░░░░░░░░░░░░░░ 16.00 %
PowerShell 3 hrs 30 mins ██▓░░░░░░░░░░░░░░░░░░░░░░ 10.27 %
SQL 3 hrs 29 mins ██▓░░░░░░░░░░░░░░░░░░░░░░ 10.20 %
JSON 1 hr 56 mins █▒░░░░░░░░░░░░░░░░░░░░░░░ 05.67 %
JavaScript 18 mins ▒░░░░░░░░░░░░░░░░░░░░░░░░ 00.91 %
INI 17 mins ▒░░░░░░░░░░░░░░░░░░░░░░░░ 00.87 %- 🔒 Closed issue #1 in mojiTMJ/mojiTMJ
- [The Heaviest AI Users Atrophy the Fastest: The Skill Atrophy Trap](https://dev.to/merbayerp/the-heaviest-ai-users-atrophy-the-fastest-the-skill-atrophy-trap-khp) Thu Jun 18 2026 4:07 AM- [Build a Real-Time Crypto Trading Dashboard with Python, React, and WebSockets](https://dev.to/marketmastersai/build-a-real-time-crypto-trading-dashboard-with-python-react-and-websockets-4i9h) Thu Jun 18 2026 4:06 AM- [Why AI Agents Will Be Bigger Than Chatbots?](https://dev.to/mr_default722/why-ai-agents-will-be-bigger-than-chatbots-1j1k) Thu Jun 18 2026 4:04 AM- [Is AI Getting Quietly Dumber? A 24/7 Benchmark That Catches LLM Degradation](https://dev.to/isray_notarray/is-ai-getting-quietly-dumber-a-247-benchmark-that-catches-llm-degradation-2g6p) Thu Jun 18 2026 3:54 AM- [Python Strings: Indexing, Slicing, and Essential String Methods](https://dev.to/tejas_shinkar/python-strings-indexing-slicing-and-essential-string-methods-3la0) Thu Jun 18 2026 3:52 AM
- 🏗️ Data platform / DataOps — metadata-driven ETL, star-schema datamarts, lakehouse on ADF + Databricks, CI/CD, governance, FinOps
- 🔧 SQL Server modernization — legacy → Azure SQL / MI / Fabric with replayable migrations
- 📊 BI / Power BI rescues — slow reports, wrong numbers, ungoverned sprawl
- 🤖 Production AI — taking LLM / RAG / agent prototypes to systems that survive Tuesday morning
- 🛡️ AI evaluation & guardrails — golden sets, drift detection, regression gates, jailbreak hardening
- ⚡ Edge AI — Azure AI Foundry Local · ONNX · on-device LLMs for latency- or privacy-bound workloads
shipping: metadata-driven datamarts & ADF pipelines on Azure for IT/EU clients
building: sqlsnapshot v2 — Azure SQL DB + Fabric warehouse coverage
exploring: production AI on Azure + on-device LLMs (Phi-3, Llama-3) via Foundry Local
reading: "Designing Data-Intensive Applications" (annual re-read)
sipping: a long espresso ☕
"Pipelines should be like good plumbing — invisible, reliable, and someone else's problem when they break. I'm the someone else."
🟢🤍🔴 Fatto con espresso ☕ & 🍕 a Milano · Ciao mondo!