Freelancer profile translated to English.
Back to original languageAbout Wessim
AWS & Azure Certified® Data Cloud Engineer
Flink | Kafka | MQTT | Airflow
Wessim Slimi, a certified Cloud Data Engineer, stands out for his exceptional versatility as a data engineering consultant, accumulating over 3 years of experience. His skills encompass a wide range of crucial technologies such as AWS, Azure, Flink, Kafka, MQTT, and Airflow.
With deep expertise in data architecture, Wessim excels in designing and deploying robust pipelines. His integrative approach emphasizes best practices in CI/CD and IaC, thereby optimizing the performance, reliability, and scalability of data processing architectures. His experience also includes leading migration initiatives to modern Cloud architectures, with particular expertise in using AWS services.
In parallel, Wessim demonstrates extensive competence in Data Science, specializing in the deployment of machine learning models. His varied technical arsenal includes tools such as Python, TensorFlow, Scikit-learn, Azure, Databricks, and PySpark.
Wessim Slimi distinguishes himself by his ability to tackle complex challenges with a holistic approach. His versatility and technical expertise make him a sought-after professional, capable of easily adapting to the diverse facets of data engineering, with an emphasis on the efficient deployment of cutting-edge solutions.
Talks about #aws, #azure, #mlops, #dataops, and #kubernetes
French
Native or bilingual
Can work on-site
Marseille (up to 50km), Paris (up to 50km), Toulouse (up to 50km), Bordeaux (up to 50km), Lyon (up to 50km)
Experience
- CMA CGMCloud Data EngineeringTRANSPORTATIONNovember 2021 - Today (4 years and 7 months)Marseille, FranceData Architecture and DataOps Consultant for CMA-CGM• Design and deploy data ingestion and processing pipelines using best practices in CI/CD and Infrastructure as Code (IaC) for Batch and Streaming environments.• Analyze and audit existing data processing architecture, and propose improvements to optimize performance, reliability, and scalability.• Lead the migration and refactoring of the old data processing architecture to a new Move to Cloud architecture on AWS, using ETL/ELT and Batch and Streaming processing technologies.• Participate in the design and implementation of a resilient, scalable, and secure data architecture using AWS Cloud services.Services and concepts mastered:• Infrastructure as Code: Terraform• Data Storage: S3, Snowflake• Security, Identity, and Compliance: AWS IAM• Data Processing: Flink, Kinesis Lambda (Serverless), EKS (Kubernetes), EC2 (VM Instance), Docker, ECR (Docker Registry), ECS (Container Orchestration), Snowflake (Data Warehouse Engine), Glue, PySpark (Big Data Processing), MQTT (streaming)• Automation: Airflow, Kubernetes CronJobs & Jobs• Development Tools: GitLab, GitLab CI, Jenkins, AWS SDK, Boto3• Languages: Python, SQL, Shell• Agile Development Methodology: SCRUM
- EDF RenouvelablesCloud ML EngineerAugust 2021 - September 2022 (1 year and 1 month)Montpellier, FranceML Engineer• Development and Deployment of predictive ML models in the field of renewable energies: Predictive Maintenance, Fault Detection, Anomaly Detection.• Implementation of various Data Pipelines: Real-time & Streaming• Deployment, productionization, and monitoring of ML models.• Technical definition of business needs, objectives, and project KPIs for Data projects.• Contribution to the implementation of the Data project Roadmap. Azure Blob ADSL Gen2 Azure ML Azure Data Factory Azure AD Python MLflow Predictive Maintenance PI OSISOFT
- EDF RenouvelablesML EngineerENERGY AND UTILITIESNovember 2012 - December 2021 (9 years and 2 months)Montpellier, FranceProduct Owner Stream Data• Organization and facilitation of continuous exchanges to develop and define business needs for Data projects.• Supervision and arrangement of the development and delivery of Data products.• Formulation and prioritization of Data needs.• Development of the Data Backlog and Roadmap.• Writing User Stories and their transcription into Features.Data Scientist• Development of Machine Learning models to meet business needs in:Predictive Maintenance:- Development of models based on Digital Twins for predicting electrical failures in Wind Turbines- Estimation of Wind Turbine age- Development of ML models for detecting icing on Wind Turbine blades using vibration dataCondition-Based Maintenance:- Contribution to the development of algorithms for detecting underperformance of an energy asset: Wind Turbine and Photovoltaic Panel- Development of algorithms for monitoring and detecting intrusion in Wind or Photovoltaic farms.Data Engineering• Implementation and creation of the various Data Pipelines used.• Deployment, Maintenance, and monitoring of the ML models used.• Scheduling of Python scripts via Chrontab or SystemCTLTechnologies used: Python, Scikitlearn, Catboost, Linux, ChronTab, SystemCTL, PI Osisoft, PI AssetFramework, PI WebAPIConcepts used:- Agile- Predictive Maintenance- Condition-Based Maintenance- Machine Learning: Regression, Classification, Clustering, Digital Twins
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Education
- Telecommunications Engineering DegreeHigher School of Communications of Tunis2019Diplôme d'Ingénieur en Télécommuni cation
- Engineering DegreeIMT Atlantique2020
Certifications
- AWS Solution ArchitectAmazon Web Services2024
- Microsoft Certified: Azure Data Scientist AssociateMicrosoft2023