Hire the Best ETL Developers
in Egypt

🔥 6+ Years of Experience in Business Data Research & Automation 🔥 500+ Successful Projects Delivered 🔥 100% Job Success Rate! 🔥 Always provide sample data upfront as proof of understanding your project's needs! If you’ve ever spent hours trying to consolidate scattered business information into something usable, I understand the frustration. I help companies turn fragmented data into clean, structured, and actionable datasets efficiently and reliably. I specialize in custom data solutions built with Python, designed around specific business objectives such as: • Lead generation and prospect research • Market and competitor analysis • Business intelligence and reporting • Data preparation for analytics and decision-making My focus is always on accuracy, structure, and usability, not just raw data delivery. 🛠 Technical Expertise Python Automation & Workflow Engineering • Python automation using Scrapy, Selenium, BeautifulSoup4 • Headless browser control (Chromium, Firefox) • Apify automation platform integration Data Visualization • Command-line tools (CLI) • Lightweight desktop applications (Tkinter, PyQt) • Web-based dashboards (Flask) • API development and deployment (FastAPI, Render) Data Processing & Structuring • Google Sheets API integration • Cloud-ready deployments (Docker, GCP, AWS, Railway, Render) • Structured outputs: Excel, CSV, JSON, SQL databases • Document processing (PDF handling, OCR, text normalization) • Asset handling (file and image processing) 🚀 Notable Projects E-Commerce Market Analysis • Prepared structured pricing, specification, and review datasets for comparative analysis. • Delivered benchmark-ready Excel reports to support market positioning decisions. Financial Document Processing • Processed client-provided financial reports (annual reports, balance sheets, income statements). • Normalized and converted data into Excel and JSON formats for immediate analysis. 🔑 Why Work With Me • Strict confidentiality and NDA support for client-provided data and systems. • Small tools delivered within 24–48 hours. • I double-check every piece of data to make sure nothing’s missing or wrong. • Robust software design that handles edge cases and input changes reliably. • I keep you in the loop with regular updates, share sample results before you commit, and stay available after the job is done. • I’ve never missed a deadline, and past clients know they can count on me for reliable delivery and maintenance. • Optional monthly maintenance for deployed tools and data workflows. • Experience working with multilingual datasets (Arabic, French, Finnish, and more). 📩 Let’s Connect Ready for clean, structured data without the headaches? Contact me to discuss your requirements—sample results provided up front so you know exactly what to expect. Python | JavaScript | Data Processing | Data Automation | Data Aggregation | API Integration | API Development | API Endpoints | cURL | Requests | AWS | Cloud Deployment | Workflow Automation | Business Intelligence | Market Research | Competitor Analysis | Lead Generation | Contact Research | CRM Data | Public Business Data | Real Estate Data | Property Records Analysis | E-commerce Research | Industry Research | B2B Research | Google SERP API Integration | Google Maps API | Google Places API | Google Business API | Google Sheets Integration | Excel | CSV | JSON | SQL Databases | Data Validation | Data Enrichment | Reporting | Analytics | Dashboarding | Document Processing | OCR Processing | Financial Data Processing | Multilingual Data | Automation Tools

As a proactive Data Engineer and Analyst with a B.S. in Computing and Data Science and hands-on experience in Azure, AWS, and advanced analytics, I deliver end-to-end data solutions that drive business growth. My expertise includes: - Cloud Engineering: Designing scalable ETL/ELT pipelines, data lakes, and warehouses using Azure (Data Factory, Synapse, Databricks) and AWS. - Advanced Analytics: Building predictive models (e.g., 10% revenue increase for The Sparks Foundation) and sentiment analysis systems (511% improvement in detection rates). - BI & Visualization: Creating interactive dashboards in Power BI and Tableau to translate complex datasets into actionable insights. - Data Infrastructure: Optimizing distributed systems, API integrations, and metadata management for seamless operations. I’ve engineered high-impact projects like the Bing News Analytics Platform (processing 85+ daily articles with real-time categorization) and the Dubizale Real Estate Analysis (transforming 300K+ listings into market trends). Certified by Microsoft’s Data Engineer Training Program and DEPI, I combine technical rigor with strategic thinking to solve data challenges efficiently. Let’s collaborate to turn your data into a competitive edge!

As a Data Engineer and Systems Developer, I build scalable data solutions and backend systems that power efficient, reliable workflows. My work focuses on designing and maintaining robust ETL/ELT pipelines, optimizing SQL and PostgreSQL databases, and implementing cloud-based data architectures across various platforms. I specialize in building backend automation that ensures data integrity, performance, and availability. With a systems-thinking mindset, I develop clean, maintainable infrastructure that supports real-time processing and actionable analytics. I’m driven by continuous improvement and delivering solutions that support data-driven decision-making at scale.

I am a Data Analyst and ETL Developer specializing in turning raw data into clean, structured, and actionable insights. I help businesses clean, transform, analyze, and visualize their data using Power BI, Excel, SQL, Python, and Azure Data Factory. My focus is on building professional dashboards, reliable reports, and automated ETL workflows that make data easier to understand and use. What I can help you with: • Data cleaning, transformation, and validation • Interactive Power BI dashboards • Excel dashboards and Pivot Table reports • SQL queries, data analysis, and reporting • Python data analysis using Pandas • ETL pipeline development • Azure Data Factory workflows • Loading data into SQL databases • KPI tracking and business performance reports • Converting raw Excel/CSV files into clean analytical datasets I recently completed an end-to-end data engineering project that included extracting data from Kaggle, transforming it with Python, building an ETL pipeline using Azure Data Factory, loading the data into Azure SQL Database, and performing SQL-based analysis. My goal is simple: turn messy data into clean insights, automated workflows, and professional dashboards that help clients make better decisions.

I'm a Data Engineer with a strong background in data warehousing, ETL pipelines, and cloud technologies. I specialize in designing scalable, end-to-end data solutions that turn raw data into actionable insights. I hold a Bachelor's degree in Data Science from Alexandria University and completed a diploma in Data Engineering at the Information Technology Institute (ITI). My technical toolkit includes Python, SQL, Power BI, AWS, Azure, and tools like SSIS, Airflow, and Databricks. I’m passionate about clean, reliable data and love tackling complex data challenges whether it’s debugging ETL jobs, optimizing queries, or designing data models. My goal is always to build solutions that are not only efficient but also meaningful for decision-making.

Hi, - Design, develop, and maintain end-to-end data analytics solutions using AWS - Azure technologies. - Engage in activities of requirement elicitation with our clientele. - Mentor junior members of the team in data engineering. - Deliver analytical solutions to clients and contribute to knowledge transfer. - Design, develop, and maintain end to end data analytical solutions using AWS technologies. - Engage in activities of requirement elicitation with our clientele. - Mentor junior members on the team in data engineering. - Deliver analytical solutions to clients and contribute in knowledge transfer. - 6+ years of experience as a data engineer. - Familiarity with analytical architectures including Data Warehouses, Data Lakes and Data Lakehouses. - Knowledge of relational engines available on AWS including Amazon RDS and Amazon Aurora. - Knowledge of NoSQL offerings on AWS (e.g. DynamoDB). - Knowledge of setting up Data Lakes on S3 using Lake Formation for governance. - Knowledge of using AWS Glue to set up catalogs, crawlers and ETL jobs. - Familiarity with the Hadoop ecosystems, including tools like Hive, Spark and Kafka. - Familiarity with using Hadoop derivative tools to perform batch analytics in Amazon EMR. - Familiarity with AWS Lambda to perform lightweight transformations. - Familiarity with governance over AWS based analytical solutions including using tools such as IAM, Macie, Cloud Watch, Cloud Trail and Step Functions. - Familiarity with using Amazon Kinesis (Firehose, Streams and Analytics) to capture and analyze data in real time. - Knowledge of setting up data warehouse solutions using Amazon Redshift. - Familiarity with Dimensional Modeling (Dimensions, Facts, Slowly Changing Dimensions, Outriggers, Role Playing Dimensions, Junk Dimensions, Degenerate Dimensions, Multi-valued Dimensions, Transactional Facts, Periodic Snapshot Facts and Accumulating Snapshot Facts). - Knowledge of implementing common ETL patterns to support data warehouse workloads. - Knowledge of using Redshift Spectrum to perform federated querying. - Knowledge of using Amazon Athena. - Strong knowledge of Python Want to work together? I’d love to hear from you. Regards, Ahmed M