Hamza L

Cloud Data Engineer

Mar 2026 - Apr 2026 • 1 mo

Multi-Cloud Data Engineering - Telecommunications Sector Design and implementation of multi-cloud data pipelines (Huawei/ AWS) in an Agile environment for large scale telecom projects: • Cloud cost analytics platform (GFR-Orange Project): Development of a multi-project consumption visualization and analysis solution based on PySpark and Apache Superset, deployed on OKS with MySQL RDS and S3 integration • DWS Decommissioning: Decommissioning of a DWS PostgreSQL database to a new S3 lakehouse architecture using Iceberg, Spark processing and Trino querying on OKS, significantly reducing costs and improving performance • ETL pipeline modernization: Refactoring and inter-instance Dataiku migration with Airflow orchestration, data streaming to S3 via Spark, and transformation for analytical consumption • GeoRéseau Tableau Proxy: Development of a Python proxy API deployed on Kubernetes enabling integration of OpenStreetMap basemaps (GeoRéso) into Tableau Server. Implementation of OAuth2 authentication with GATAPE/ OKAPI, JWT token management • Containerized orchestration: Deployment and management of cloud-native data workloads on Kubernetes with optimized continuous integration • Huawei Paris Training: Complete migration of legacy infrastructure from Huawei Flexible Engine (public) to a modern Huawei Cloud Stack architecture (private) • SMOT (SDN Monitoring of Tomorrow): Migration of more than 200TB per year of historical data (1 year) from JSON files in S3 to Parquet to optimize storage and query performance, followed by ingestion into a ClickHouse database. Deployment of a ClickHouse analytical platform on Kubernetes, using Rust and PySpark for high-performance data ingestion and transformation.

Data Platform Engineer

Aug 2024 - Mar 2025 • 7 mos

Big Data Consultant within the Data Office/Factory Team of a Client (Banking Sector) •Collaborated closely with business stakeholders and IT teams to identify and gather critical data from various operational systems of the bank using Sqoop. •Designed and implemented a robust Data Lake leveraging the Medallion Architecture with Hadoop, Hive, and Hue, providing a centralized and structured repository. Worked with business units to define data quality standards and governance policies. Processed and transformed data using Spark Scala, ensuring usability for analytics and reporting. •Partnered with business leads to design and implement a Data Mesh. •Internal Mission: Building a Data Platform with Infrastructure as Code (IaC) for different clients Building a modular Data Platform with diverse stacks and tools as IaC to standardize and streamline data platform deployment across various client environments. •Designed the platform to support both cloud-based clients using AWS and on-premises setups, accommodating a variety of client requirements and infrastructure. Data platform Engineer – Full Data Platform Implementation with IaC (Lead Role) •Led the end-to-end implementation of a complete Data Platform using Ansible-based IaC for a strategic client. •Integrated key technologies: Apache Spark, dbt, Dremio, Minio, Apache Iceberg, Apache Airflow, Prometheus and Grafana •Oversaw and coordinated a cross-functional team of client data engineers and analysts, ensuring timely delivery, high-quality engineering practices, and alignment with business goals

Microsoft Data Engineer - Azure

Feb 2024 - Aug 2024 • 6 mos

Implementation of a Modern Decision Support System for Techsub Managem (Energy/Mining Sector) Designed and implemented a decision support system on Azure Cloud to monitor and manage operational performance indicators across multiple sites in Africa. Built multiple pipelines using Azure Data Factory and Databricks for data ingestion and orchestration. • • Utilized pyspark for data transformations and quality controls across the bronze, silver, and gold layers of the data lakehouse. • Centralized data in Azure Synapse Analytics and developed actionable Power BI reports for decision makers. Implemented Azure DevOps pipelines to automate deployments and ensure operational efficiency.