Data Analyst — Abu Dhabi, UAE

From raw rows to decisions people trust.

I build the pipeline underneath the dashboard — cleaning, modeling, and warehousing data with SQL Server, Python, and Power BI, so the numbers hold up when someone actually acts on them.

RAW CSV · SQL CLEANED Validated SERVED Dashboard
Bronze — Raw Input

Who I am

I'm a Statistics graduate who fell for the unglamorous half of data work — the cleaning, the modeling, the warehouse architecture nobody sees but everything depends on. I work across SQL Server, Python, Power BI, and Tableau, building using Kimball star schemas and Medallion (Bronze / Silver / Gold) pipelines, because a dashboard is only as trustworthy as the data flow underneath it.

My path started in a statistics classroom in Khartoum and ran through a national household survey and an airline's operations desk before landing here in Abu Dhabi. Along the way I learned that the most useful question in any dataset usually isn't the one you started with — while digging into three years of global layoff data, I found that a company's layoff risk had almost nothing to do with funding raised, and everything to do with whether it was publicly traded.

That's the kind of finding raw numbers hide until someone asks the right question. I'm currently looking for a Data Analyst role where I can bring that same mix of statistical rigor and hands-on engineering to a messy dataset or a dashboard that isn't telling the story it should.

2,361
Layoff records analyzed across 51 countries to test what actually predicts mass layoffs
2,000+
Displaced households surveyed and structured into insights for real program decisions
15%
Improvement in resource allocation efficiency from booking-pattern analysis at Al Karama Aviation
Silver — Refined

What I work with

Warehousing & ETL

  • SQL Server / T-SQL
  • Medallion architecture
  • Kimball star schema
  • MySQL
  • Data cleaning & validation

Analysis & Visualization

  • Power BI (DAX)
  • Tableau
  • Python (Pandas, Matplotlib, Seaborn)
  • Excel (advanced)
  • KPI reporting & dashboards

Statistical Methods

  • SPSS / R / Minitab
  • Hypothesis testing
  • Regression & forecasting
  • Correlation analysis
  • Quantitative research design
Silver — Refined

Experience

Data Analyst Assistant / Operations Support
Al Karama Aviation, Khartoum
Feb 2023 — Feb 2024
  • Conducted statistical analysis on flight operations and passenger data using SPSS and R, delivering insights to senior management.
  • Designed and maintained interactive dashboards in Python (Matplotlib/Seaborn), Excel, and Power BI to monitor KPIs and service performance.
  • Analyzed booking patterns and customer behavior, contributing to a 15% improvement in resource allocation efficiency.
  • Managed and optimized operational databases in MySQL, ensuring data quality for financial and operational reporting.
Data Analyst Trainee
Central Bureau of Statistics, Sudan
Mar 2022 — Oct 2022
  • Collected, cleaned, and structured survey data from 2,000+ displaced households for official reporting.
  • Built analytical reports and dashboards in Excel and Power BI to support evidence-based program decisions.
  • Identified that 72% of surveyed individuals were internally displaced, informing targeted planning.
  • Applied descriptive and inferential statistics to interpret survey findings for stakeholders.
Gold — Served

Projects

01 / WAREHOUSE

Sales Data Warehouse

A CRM/ERP sales data warehouse built from scratch on SQL Server using Medallion architecture — Bronze for raw landed CSVs, Silver for cleansing and enrichment, Gold for a Kimball star schema (dim_customers, dim_products, fact_sales) ready for BI consumption.

SQL ServerT-SQLETLKimball
View on GitHub ↗
02 / ANALYSIS

World Layoffs 2020–2023

End-to-end analysis of 2,361 global layoff events across 51 countries. Found that funding raised barely correlated with layoff size (r = 0.077) — while publicly-traded companies accounted for 45% of all layoffs in the dataset. Delivered as a 5-page Power BI dashboard plus a D3.js interactive map.

SQL ServerPower BIPythonD3.js
View on GitHub ↗
03 / FORECAST

Post-Hajj Travel Demand, Khartoum

A forecasting study for Al Karama Aviation modeling expected passenger movement, peak travel periods, and key routes into and out of Khartoum following the Hajj season, to support transportation planning and operational readiness.

ForecastingSPSSR
Internal case study — details on request
Bronze — Foundation

Education

B.Sc. in Statistics

Sudan University of Science and Technology, Khartoum
Nov 2018 — Oct 2023
3.06GPA / 4.0
Coursework: Time Series Analysis, Data Mining, Regression Analysis, Biostatistics, Econometrics, Multivariate Analysis, Statistical Inference, Database Systems, Experimental Design, Sampling Distributions — 190 credit hours over five years.

Have a dataset that isn't telling the story it should?

I'm open to Data Analyst and BI Analyst roles across the UAE — send me a message, I'd love to hear about it.