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: 25 July 2026 - To: 01 August 2026
Total Time: 11 hrs 33 mins
Markdown 5 hrs 12 mins ███████████▒░░░░░░░░░░░░░ 44.67 %
Python 3 hrs 1 min ██████▓░░░░░░░░░░░░░░░░░░ 26.03 %
Text 1 hr 16 mins ██▓░░░░░░░░░░░░░░░░░░░░░░ 10.91 %
SQL 54 mins ██░░░░░░░░░░░░░░░░░░░░░░░ 07.75 %
JSON 32 mins █▒░░░░░░░░░░░░░░░░░░░░░░░ 04.72 %
Docker 30 mins █░░░░░░░░░░░░░░░░░░░░░░░░ 04.41 %
PowerShell 4 mins ░░░░░░░░░░░░░░░░░░░░░░░░░ 00.65 %
- 🔒 Closed issue #1 in mojiTMJ/mojiTMJ
- [One locale code silently killed 92% of a Magento Shopware migration — and the tool reported Done](https://dev.to/yuriydne/one-locale-code-silently-killed-92-of-a-magento-shopware-migration-and-the-tool-reported-done-4l6j) Mon Aug 03 2026 2:40 PM- [What are your goals for the week? #190](https://dev.to/jarvisscript/what-are-your-goals-for-the-week-190-d5p) Mon Aug 03 2026 2:39 PM- [OWASP Top 10: The Web's Most Critical Security Risks](https://dev.to/rhuturaj_takle/owasp-top-10-the-webs-most-critical-security-risks-5clo) Mon Aug 03 2026 2:33 PM- [Behind the scenes: How we build, test, and scale Google Agent Skills](https://dev.to/googleai/behind-the-scenes-how-we-build-test-and-scale-google-agent-skills-1am5) Mon Aug 03 2026 2:33 PM- [PomoEfficiency, an alternative pomodoro timer](https://dev.to/guealdev/pomoefficiency-an-alternative-pomodoro-timer-340m) Mon Aug 03 2026 2:26 PM
- 🏗️ 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!