Data Engineer | Azure, Databricks & Power BI
I'm a Data Engineer with hands-on, production experience building ETL pipelines, cloud data warehouses, and BI dashboards that help businesses turn raw, messy data into clear, actionable insights.
In my role at DEPI, I built ETL pipelines on Azure/Databricks using the Medallion architecture, optimizing a data warehouse to support real analytics use cases. I developed CI/CD pipelines and dimensional models that reduced release cycles by 60%, and created Power BI dashboards that visualized KPIs for data-driven decision making across the business. I also completed cloud architect training covering Azure, AWS, and GCP fundamentals, where I designed scalable, cost-effective cloud architectures and automated infrastructure provisioning using Terraform.
Beyond my formal role, I've built independent projects covering the full data engineering lifecycle including an end-to-end pipeline that scraped and ingested data from multiple sources, transformed it using Spark into optimized Parquet storage on Azure Data Lake, and delivered Power BI dashboards visualizing financial metrics. I've also worked on multi-cloud infrastructure projects across Azure, AWS, and GCP, applying best practices in IAM, monitoring, high availability, and disaster recovery using Terraform and CI/CD automation.
My technical toolkit includes Python, SQL, PySpark, Spark SQL, R, Java, and C++, along with tools like Docker, Airflow, Kestra, Jenkins, GitHub Actions, Snowflake, PostgreSQL, MongoDB, and SQL Server. I hold certifications in Microsoft Azure Data Engineering and AWS Cloud Architecting, and I'm a Bachelor's graduate in Computer and Data Science from Alexandria University (GPA 3.62).
I care about building systems I fully understand and can maintain not just quick fixes. Whether it's a one-time data cleanup and analysis, a fully automated ETL pipeline, or ongoing DevOps/DataOps support, I bring a structured, end-to-end approach: clean data in, reliable automation throughout, and clear insights out.
I'm available and ready to start working with you right away let's talk about how I can help with your data needs.
Work Terms
Availability: I'm available to work 10–40+ hours per week and can adjust my schedule to overlap with your team's time zone for calls and syncs.
Communication: I respond promptly (usually within a few hours) and prefer clear written updates alongside scheduled calls for project check-ins. I'm comfortable with Slack, email, or your preferred communication tool.
Process: For new projects, I start with a short discovery call or written brief to fully understand your data, systems, and goals before beginning work. I provide regular progress updates and welcome feedback throughout the engagement rather than only at the end.
Deliverables & Revisions: I aim to deliver clean, well-documented work (pipelines, dashboards, or reports) that's easy for your team to understand and maintain. I'm happy to make reasonable revisions to ensure the final result meets your expectations.
Payment: I work on an hourly or fixed-price basis depending on project scope happy to discuss what works best for your engagement. Milestone-based payments are welcome for longer projects.
Tools & Access: For pipeline or cloud work, I'll need appropriate access credentials (read-only where possible) to relevant systems I follow best practices for data security and will discuss access scope before starting.