About Khalil
French
Native or bilingual
English
Fluent
Arabic
Native or bilingual
German
Basic
Experience
- BNP ParibasData EngineerMarch 2023 - Today (3 years and 4 months)Paris, France• Delivered and maintained over 20 data engineering projects with varying complexity, performance constraints, and regulatory requirements, within the DataHub team supporting multiple bank entities.• Designed and developed end-to-end ingestion and transformation pipelines, collaborating with business analysts and technical teams to refine needs and ensure smooth production deployments.• Preprocessed and transformed raw data into usable formats, ensuring smooth routing across different S3 layers using Python and PySpark.• Alpha-tested local generative AI models and provided feedback to improve their performance, and used assistants to accelerate pipeline development and documentation on 10+ projects.• Implemented automated data quality checks and report generation to ensure data reliability and governance.• Optimized the performance of existing processes across multiple concurrent projects, drastically reducing processing times and improving overall system efficiency.• Proactively designed and developed automation tools used by 40+ users in 4 countries, eliminating manual tasks and accelerating deployments. accelerating production releases.TECHNOLOGIES: Python, Pyspark, SQL, Microsoft SQL Server, Git, Bitbucket, Jenkins, S3, Autosys, Docker, Local LLMs, Jira
- APTEAData EngineerSeptember 2022 - February 2023 (5 months)Paris, France• Designed an end-to-end data extraction pipeline and an API to analyze text and style elements of unstructured documents, transforming them into schemas for template-based generation.TECHNOLOGIES: Python, Pandas, Text processing, Git, Flask, Postman
- ValueData EngineerOctober 2021 - August 2022 (10 months)Tunis, Tunisia• Built an enterprise Data Warehouse from scratch for BIAT's Risk and Banking Operations teams by designing scalable pipelines (Pyspark, Talend) to process vast volumes of financial data.• Delivered bi-weekly demos to banking stakeholders, ensuring alignment and transparency throughout the project.• Orchestrated the ingestion and transformation of complex data from multiple banking platforms (Oracle, Temenos T24, SWIFT APIs), converting unstructured XML streams into optimized Data Warehouse schemas.• Proactively designed Python tools that reduced development cycles by up to 10x, limited human errors, and enabled exhaustive validation detecting anomalies invisible through manual QA.• Redesigned the architecture to introduce parallel processing, reducing processing windows by up to 6x while applying strict data encryption and confidentiality standards.
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Education
- Computer Engineering DegreeENSIIE, National School of Computer Science for Industry and Business2019Cycle d'ingénieur en informatique
- Master M2 TRIED in Big DataUniversité Paris Saclay2019Master M2 TRIED en big data