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"],
};|
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: 29 May 2026 - To: 05 June 2026
Total Time: 6 hrs 34 mins
PowerShell 2 hrs 10 mins ███████░░░░░░░░░░░░░░░░░░ 27.37 %
XML 1 hr 48 mins █████▓░░░░░░░░░░░░░░░░░░░ 22.72 %
Batchfile 1 hr 3 mins ███▒░░░░░░░░░░░░░░░░░░░░░ 13.36 %
SQL 33 mins █▓░░░░░░░░░░░░░░░░░░░░░░░ 07.07 %
Markdown 28 mins █▒░░░░░░░░░░░░░░░░░░░░░░░ 05.95 %
INI 17 mins █░░░░░░░░░░░░░░░░░░░░░░░░ 03.75 %
Python 9 mins ▓░░░░░░░░░░░░░░░░░░░░░░░░ 02.01 %- 🔒 Closed issue #1 in mojiTMJ/mojiTMJ
- [On-Device Debugging And JUnit 5](https://dev.to/codenameone/on-device-debugging-and-junit-5-245) Sat Jun 06 2026 1:32 PM- [Using Symfony Forms as Controller Arguments with #[MapRequestToForm]](https://dev.to/azyouness/using-symfony-forms-as-controller-arguments-with-maprequesttoform-52ol) Sat Jun 06 2026 1:32 PM- [A 120B-model laptop, a federal AI bill, and free pro-grade editing: 3 shifts for builders](https://dev.to/danio_dev/a-120b-model-laptop-a-federal-ai-bill-and-free-pro-grade-editing-3-shifts-for-builders-36nb) Sat Jun 06 2026 1:30 PM- [LLM-Assisted Deploy: You Save Typing, Not Thinking](https://dev.to/s_a_shkuratov/llm-assisted-deploy-you-save-typing-not-thinking-5h91) Sat Jun 06 2026 1:24 PM- [Cron Syntax Explained: The 5 Fields and the Expressions You'll Actually Use (with a free generator)](https://dev.to/forglydev/cron-syntax-explained-the-5-fields-and-the-expressions-youll-actually-use-with-a-free-generator-58k6) Sat Jun 06 2026 1:22 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 ☕

