Anass NABIL

- Migrated a production SAS ETL pipeline to Python, reducing execution time by approximately 20× while enhancing maintainability and reliability. - Built scalable data ingestion pipelines from multiple sources, including Web Scraping, REST APIs, relational databases, and third-party platforms. - Developed business intelligence dashboards and automated reporting solutions for automotive leasing market benchmarking and competitive analysis.

Contributing to the development of a cloud-native data platform on AWS designed to help organizations unlock the value of their data. The platform covers the full data lifecycle from ingestion to visualization with a strong focus on scalability, automation, and reliability : - serverless data ingestion pipelines with AWS Lambda and a custom lightweight ingestion engine called Hermes. - A modern data lake architecture on Amazon S3 with Apache Iceberg for reliable, performant, and ACID-compliant storage. - Modular transformation workflows using dbt and SQL, orchestrated with AWS ECS. - Supporting interactive data exploration through Zellij (Open-data-viz), an open-source dashboarding framework. - Maintaining infrastructure consistency and automation using Terraform (IaC). - Ensuring collaborative, version-controlled development through Git. - Setting up CI/CD pipelines to automate testing, deployment, and delivery.

helped me get this job

- Designed and developed a cross-platform mobile application for locating on-duty pharmacies based on users’ real-time location. - Integrated geolocation APIs, mapping services, and pharmacy scheduling data to deliver accurate and reliable search results. - Built a responsive, user-friendly interface to improve accessibility to emergency healthcare services.