Khaled is available for hire
Hire KhaledKhaled Othman
Verified Expert in Engineering
Data Analyst and Developer
Cairo, Cairo Governorate, Egypt
Toptal member since January 9, 2024
Bio
Khaled is a results-oriented data analyst. He has a track record in leveraging Python for data automation and implementing robust data warehouses. Khaled's expertise lies in optimizing data for predictive, comprehensive insights—fostering informed decision-making for business growth.
Portfolio
Carina Wear
SQL, Python, Web Scraping, Data Analysis, Retail & Wholesale, ETL
Epsilon AI
Python, SQL, Microsoft Power BI
Ego Egypt
SQL, Python, Data Warehousing, Data Analysis, Retail & Wholesale
Experience
- Microsoft Power BI - 4 years
- Python - 4 years
- SQL - 3 years
- Excel 365 - 3 years
- Data Analysis - 3 years
- Data Warehousing - 2 years
- Query Optimization - 2 years
- Apache Airflow - 1 year
Availability
Full-time
Preferred Environment
Data Analysis
The most amazing...
...thing I've done is automate a diverse data source collection with Python—enabling streamlined analytics and seamless data integration for thorough insights.
Work Experience
Senior Data Analyst
2022 - PRESENT
Carina Wear
- Improved refresh time from one and a half hours to 40 minutes. I optimized the dynamic Power BI reports pipeline by applying indexing and partitioning and implementing incremental refresh—enhancing data accessibility and report performance.
- Ensured efficient and error-free data processing for comprehensive analytics and insights by automating data collection and transforming cleansing processes for a weekly update of 100 files using Python.
- Enhanced real-time decision-making by conducting ad hoc analyses, providing immediate insights crucial for informed business strategies and swift responses to market dynamics.
- Implemented ML models to optimize inventory management, leveraging demand forecasting based on the true rate of sale to streamline operations—ensuring efficient stock levels, minimizing shortages, and maximizing sales opportunities.
- Spearheaded web scraping initiatives to extract valuable data from the apparel retail market, encompassing a comprehensive analysis of 10,000 items.
Technologies: SQL, Python, Web Scraping, Data Analysis, Retail & Wholesale, ETL
Data Analyst Instructor
2024 - 2025
Epsilon AI
- Trained 100+ students in Python for data analysis, Power BI, and SQL, equipping them with practical skills in data manipulation, visualization, and querying for real-world applications.
- Guided students in building end-to-end data analysis projects, helping them apply industry best practices and enhance their problem-solving skills.
- Trained 50+ students in Python, Power BI, and SQL, developed hands-on projects for practical learning and created interactive exercises to boost engagement and comprehension.
Technologies: Python, SQL, Microsoft Power BI
Data Analyst
2021 - 2022
Ego Egypt
- Executed the establishment of a robust data warehouse, enabling centralized data storage and streamlined analysis for enhanced decision support.
- Produced insightful reports for stakeholders, drawing from in-depth market analyses to identify future opportunities for brand development.
- Spearheaded the digitization of diverse company data sources, fueling comprehensive sales growth analysis and strategic decision-making.
Technologies: SQL, Python, Data Warehousing, Data Analysis, Retail & Wholesale
Experience
Data Warehouse Practice
https://github.com/KhaledBenOthman/DWH-Practice/tree/main/DWHA complete data warehouse implementation—from database setup and staging to deployment and adoption.
1. Database setup – Created the initial database objects for staging (ADV_STG) and the data warehouse (ADV_DWH).
2. Staging database – Developed the staging SQL scripts, establishing staging tables for data processing.
3. ETL process setup – Implemented the ETL process using SQL Server Integration Services (SSIS). I used SSIS to extract data from the source and load them into staging. I also created related views—product, product category, subcategory—for data coherence.
4. Data warehouse development – Formulated SQL scripts to build data warehouse tables.
5. ETL to data warehouse – Applied the ETL process from staging to the data warehouse using SSIS. I deployed SQL stored procedures for data retrieval and loading and adopted incremental loading strategies for fact tables to handle new transactions.
1. Database setup – Created the initial database objects for staging (ADV_STG) and the data warehouse (ADV_DWH).
2. Staging database – Developed the staging SQL scripts, establishing staging tables for data processing.
3. ETL process setup – Implemented the ETL process using SQL Server Integration Services (SSIS). I used SSIS to extract data from the source and load them into staging. I also created related views—product, product category, subcategory—for data coherence.
4. Data warehouse development – Formulated SQL scripts to build data warehouse tables.
5. ETL to data warehouse – Applied the ETL process from staging to the data warehouse using SSIS. I deployed SQL stored procedures for data retrieval and loading and adopted incremental loading strategies for fact tables to handle new transactions.
Python Purchasing App Simulation
I crafted a Python app, including basic account creation, dynamic market browsing, and seamless item selection. In this app, users can easily choose items, and the application calculates total bills, factoring in taxes and discounts. My focus was on ensuring data security and modularity, laying the groundwork for future enhancements.
Scraping Apparel Brands
I successfully executed a large-scale scraping project, gathering data from over 10,000 items spanning three brands. After meticulously cleaning and processing the data, I designed a dynamic dashboard to provide comprehensive insights. The result was the swift and efficient delivery of actionable analytics.
Certifications
MARCH 2025 - PRESENT
Modernizing Data Lakes and Data Warehouses with Google Cloud
Google Cloud | via Coursera
FEBRUARY 2025 - PRESENT
Data Engineering Foundation
Informatica
OCTOBER 2022 - PRESENT
Exploring and Preparing your Data with BigQuery
Google Cloud | via Coursera
JANUARY 2022 - PRESENT
Python
Kaggle
DECEMBER 2021 - PRESENT
Launching into Machine Learning
Google Cloud | via Coursera
NOVEMBER 2021 - PRESENT
How Google does Machine Learning
Google Cloud | via Coursera
OCTOBER 2017 - PRESENT
Python Core
Sololearn
Skills
Tools
Microsoft Power BI, Apache Airflow, Tableau, BigQuery
Languages
Python, SQL
Paradigms
ETL
Industry Expertise
Retail & Wholesale
Other
Data Warehousing, Web Scraping, Data Analysis, Excel 365, Query Optimization, Dashboards, Data Engineering
Collaboration That Works
How to Work with Toptal
Toptal matches you directly with global industry experts from our network in hours—not weeks or months.
1
Share your needs
Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2
Choose your talent
Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3
Start your risk-free talent trial
Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.
Top talent is in high demand.
Start hiring