Azure Data Engineer

As a Data & Cloud Engineer, I'am responsible for designing, implementing, and managing data and infrastructure solutions on Azure, with a focus on performance, scalability, and security.

Key Responsibilities:

• Designed and deployed cloud-based data solutions using Azure services.

• Transformed and secured enterprise data while ensuring high availability and optimal performance.

• Analyzed business data requirements and proposed scalable architectural solutions.

• Contributed to the design and deployment of secure and resilient cloud infrastructure.

• Developed robust, scalable, and fault-tolerant data pipelines.

• Built ETL/ELT processes for integrating, transforming, and migrating data from multiple sources.

• Implemented version control systems and CI/CD pipelines.

• Administered and optimized relational and non-relational databases.

• Managed Data Lakes and Data Warehouses for large-scale analytics.

• Ensured data quality through cleansing, validation, and governance mechanisms.

• Monitored data system performance and optimized queries for efficiency.

• Applied security best practices, including encryption, access control, and anomaly detection.

• Ensured compliance with data protection regulations (GDPR, HIPAA).

• Provided technical support and troubleshooting for data and infrastructure solutions across VMs, containers, PaaS, and API Management.

• Documented architectures, processes, and implemented solutions.

• Maintained effective communication with internal teams and clients.

Clients: GazelEnergie, Unicem

Cloud Architect / Business Analyst

Worked on the design, development, and deployment of data systems, pipelines, and cloud infrastructure with a focus on performance, security, and automation.

Databases

• Designed, developed, and maintained relational database systems (MySQL, PostgreSQL).

• Extracted data from primary and secondary sources (RDBMS, Excel models, APIs, Financial Data).

• Restructured data to improve readability and optimize usability.

• Implemented non-regression testing (CI/CD) to ensure the quality of historical data after updates.

• Designed backup strategies, encrypted data at rest and in transit, and implemented database recovery solutions.

• Centralized financial data across all environments.

Pipelines and Data Processing

• Designed and automated ETL pipelines for data extraction, transformation, and loading from various sources via frontend interfaces.

• Analyzed and corrected errors in data pipelines; identified and resolved data discrepancies.

• Automated data extraction and processing for clients through backend and frontend configurations.

• Analyzed and corrected logs related to data and code pipelines.

APIs and Integrations

• Extracted data via APIs (REST, built with Django and Flask), and developed backend interfaces to interact with external APIs.

• Developed features and integrated APIs with databases and analytics systems.

Data Visualization and Analysis

• Used statistical methods to analyze client data, identify patterns and trends for diagnostics and forecasting.

• Automated the creation of financial projection reports based on analyzed data.

• Specified and built segmented reports for insurers/reinsurers to track projections and KPIs by population.

• Created interactive visualizations for insights on populations, transactions, projections, and historical data.

Cloud Storage

• Transferred reports via SFTP to external client endpoints.

• Used AWS Lambda, S3, and CloudWatch to monitor metadata and detect anomalies in backups (corruption attempts, attacks).

• Designed and implemented storage solutions in AWS S3 for critical reports and data.

• Used RDBMS, S3, and Cassandra to store raw and transformed data.

Cloud Infrastructure

• Designed and deployed cloud infrastructures (VMs, Containers, streaming services, subnetting, network security protocols) using AWS (EC2, RDS, ECS, VPC, Security Groups).

• Migrated environments from DigitalOcean to AWS (Lift-and-Shift or AWS-native solutions).

• Automated cloud environments for clients, including permissions management, resource provisioning, and network configuration (IAM, Route 53, Ansible).

Cloud Security

• Implemented security strategies (IPS/IDS, firewalls, IAM, MFA, Subnetting, NAT).

• Encrypted data at rest and in transit in cloud environments.

• Defined and managed access permissions for users and services, internally and externally.

Software Development and Package Management

• Managed reporting software using JavaScript, XML, and ETL tools; developed and integrated interfaces for databases.

• Debugged and tested code versions; validated specific features before deployment in client environments (training, integration, production).

• Prepared and presented POCs for new clients, including analysis of their data systems, process automation, and cloud migration.

Project Management and Financial Analysis

• Analyzed longevity swap models (Fixed Leg, Collateral, Floating Leg); automated differential reports per population (using Agile, Jira, Confluence, VBA).

• Set up parallel systems for large-scale data processing; monitored and corrected discrepancies in logs and pipelines.

Clients: PIC, SCOR, AVIVA, MetLife, JUST, ZURICH, Munich RE, Phoenix

G-Research Crypto Forecasting

I forecasted the values of 14 major cryptocurrencies by developing predictive models from scratch. I utilized Python for data retrieval and preprocessing and created recurrent neural networks (RNNs) to predict cryptocurrency values. Leveraging TensorFlow and Keras, I developed innovative prediction methods and tested them to minimize errors. I validated these methods on real-time data and evaluated results over time, applying skills in Keras, Python, predictive modeling, artificial intelligence (AI), big data, TensorFlow, deep learning, and Apache Spark.

Data Assimilation Intern

During my internship at the Institut de Mathématiques de Toulouse, I analyzed Covid-19 data and collected and preprocessed data from various countries. I developed a regression model and a statistical SIRD (Suspected, Infected, Recovered, Death) model using the implicit Euler method to predict health states. I also used a neural network to predict mortality and recovery rates, leveraging my skills in Keras, Python, recurrent neural networks, crisis management, TensorFlow, mortality analysis, and epidemiology.

Data Scientist

During the Defi IA 2022 with MeteoNet and INSA Toulouse, I utilized MeteoNet data and my expertise in Python to predict daily precipitation. I preprocessed and cleaned data to make it usable, and created a recurrent neural network (RNN) to forecast future precipitation. I adapted the model to the data format for accurate future predictions, leveraging my skills in artificial intelligence (AI), statistical data analysis, and predictive modeling.

Mathematics Research Intern

I delved deeply into the inverses of Drazin and their generalizations, mastering their theory and applications in algebraic structures. I developed expertise in extending traditional inverse concepts and linking spectral theory to algebraic properties. I applied these advanced concepts to solve complex Markov chain problems, enhancing my understanding of their dynamics. My passion for pure mathematics and functional analysis drove me to utilize and implement generalized inversibility techniques to tackle challenging issues.

Linear Regression and Analysis of Variance

During my internship at LAGA, I passionately applied linear regression and ANOVA to uncover insights and evaluate statistical differences. Mastering descriptive statistics and ARMA models, I forecasted and understood complex data trends. With proficiency in R for advanced analysis and Excel for data visualization, I rigorously validated hypotheses and expertly modeled time series to reveal hidden patterns and cyclical behaviors.