BI and dashboards that save time
Semantic models and Power BI dashboards teams rely on every day. 30+ reports across 40+ locations that save 50+ hours of manual analysis a week.

I own delivery across the full stack, from SQL and data modeling to the dashboards and AI assistants people actually use, and it shows in the numbers.
Semantic models and Power BI dashboards teams rely on every day. 30+ reports across 40+ locations that save 50+ hours of manual analysis a week.
Automated ETL and star-schema models, from SQL through to the dashboard. Production pipelines that returned 210+ hours a month to operations.
LLM assistants that turn plain-language questions into governed SQL, scoped per user by row-level security. AI workflows that let people query data in plain words.
End-to-end analytics on Azure, provisioned as code and reproducible from scratch with a single command.
Each one shipped end to end, with a live demo you can open right now.
Finance and Trading
An end-to-end, cloud-native analytics platform built solo on Azure: a SQL star schema with nightly pre-aggregation, a Power BI semantic model (52 DAX measures, 5 pages, row-level security), and an AI assistant that turns plain-language questions into governed SQL. Provisioned entirely as code.
Weather and Climate
An end-to-end weather analytics pipeline for 5 Romanian cities, designed as an AWS serverless architecture and shipped as a runnable local-first stack, with a 4-page interactive dashboard.
Retail and E-commerce
An end-to-end analytics pipeline on 1M+ UK e-commerce transactions: Python ETL into SQL Server, modeled in Power BI with a DAX calendar and interactive sales, country and trend dashboards.
Energy and Utilities
A 3-page Power BI report analysing electrical energy consumption across phases L1, L2 and L3 at daily and monthly granularity, with KPI cards, energy indicators and interactive filters.
Manufacturing
An interactive Power BI dashboard to monitor equipment downtime in a manufacturing setting, broken down by activity type, priority and asset, helping maintenance teams prioritise interventions.
Hands-on domain knowledge from work and applied projects across sectors.
Multi-location sales, cost, inventory and labour analytics across 40+ restaurants.
Production, downtime and quality analytics for automotive safety systems.
Manufacturing KPIs and reporting for smart parcel-locker production.
Trading-desk performance, risk and behavioral analytics.
Customer, sales and order analytics on 1M+ transactions.
Hourly weather analytics and activity scoring for 5 cities.
I build analytics systems that cut reporting friction and turn fragmented data into decisions teams can act on. With 4+ years as a Data Analyst and BI Developer, I connect business needs to reliable data: automated pipelines, standardized KPIs, Power BI dashboards and AI-assisted workflows.
Lately I have gone deeper on cloud-native and AI: Azure, automation and LLM-powered workflows that let people ask questions of their data in plain language. I care about making data easy to trust and genuinely useful, from the model underneath to the dashboard people open.
BSc, Computer Science
Faculty of Mathematics and Informatics. Bachelor's thesis: TCP, an end-to-end cloud-native analytics platform on Azure with a Power BI model and an AI assistant (the latest project above).
Medical Informatics, Erasmus
Erasmus exchange semester in Germany: databases, applied statistics and health data analysis, all coursework in English within an international cohort.
Open to data, BI and AI-analytics roles. The best way to reach me is LinkedIn or GitHub.