About Julien
- In-depth expertise in **AWS**, **DevOps**, **SRE**, and **Data environments**.
- Proactive and autonomous, I adapt equally well to small-scale contexts and larger environments.
- Open toshortorlongmissions, depending on client needs.
- Proven experience in managing complex infrastructures, particularly inautomationandoptimizationof workflows on Kubernetes and AWS.
- Curious and constantly learning, I am always looking for new technologies to explore.
French
Native or bilingual
English
Fluent
Japanese
Basic
Experience
- Treezor - Enable Creative BankingSite Reliability EngineerBANKING AND INSURANCENovember 2023 - August 2024 (9 months)Paris, FranceContext and Objectives:In a context of rapid growth, the central objective was to ensure the resilience of the AWS infrastructure while making architectural adjustments to meet new company requirements and optimize team productivity.Missions and Achievements:
- **Definition and implementation of DevOps best practices**:
Implementation of standards and best practices for infrastructure automation and CI/CD pipelines to improve deliverable quality and reduce human error.- **Improvement of AWS infrastructure**:
Maintenance and optimization of AWS infrastructure by improving resilience and ensuring the availability of critical services, particularly through disaster recovery solutions aligned with RTO and RPO objectives.- **Evaluation and improvement of Terraform, Python, Golang scripts**:
Review, optimization, and modernization of existing scripts for better automation and resource management.- **Proposal of architectural improvements**:
Design and implementation of a multi-region architecture (Warm Stand By) to increase service redundancy and resilience, thereby minimizing failure risks and reducing downtime.- **Support for development teams**:
Accompanying development teams by providing continuous technical support and resolving critical incidents to quickly meet operational needs.Technical Environment:*CloudAWS: S3, Lambda, EC2, VPC, Route53, API Gateway, RDS, KMS, DynamoDB- **Tools**: Kubernetes, GitLab, GitLabCI
- **Languages**: Terraform, Golang, Python
- Devoteam RevolveDevOps Architect at LexisNexisLEGALMarch 2023 - November 2023 (8 months)Paris, FranceContext and Objectives:In a context of strong competition in online legal services and evolving regulations, improving the AWS infrastructure was a central issue. The implementation of a Disaster Recovery Plan (DRP) was my main objective.Missions and Achievements:
- **Maintenance of existing infrastructure**:
Proactive management of the current infrastructure, including bug fixing and problem resolution to ensure the stability and security of production systems.- **Resilience improvement with Terraform and Kubernetes**:
Optimization of Terraform and Python scripts to strengthen AWS infrastructure automation, improve their performance, and harmonize practices for increased long-term maintainability.- **Design and implementation of a resilience solution (DRP)**:
Design and deployment of a backup centralization and disaster recovery solution, aligning the infrastructure with business continuity objectives (RTO, RPO).- **Streamlining CI/CD pipelines with Azure DevOps and ArgoCD**:
Integration and optimization of CI/CD pipelines, using Azure DevOps and ArgoCD, to automate deployments and reduce human errors.Technical Environment:- **Tools**: Kubernetes, Azure DevOps, ArgoCD
- **Languages**: Terraform, Python
- **Databases**: Elasticsearch, MongoDB
- **AWS Cloud**: S3, Lambda, EC2, VPC, Route53, RDS, KMS
- Devoteam RevolveDevOps & Data Tech Lead at M6PRESS AND MEDIAMarch 2021 - February 2023 (1 year and 11 months)Paris, FranceContext and Objectives:The objective was to develop a new data platform enabling M6 to better leverage its data, while ensuring secure and cost-optimized access. This infrastructure also needed to support the development of AI models by providing clean and easily accessible data to the teams.Missions and Achievements:
- **Identification of business needs**:
Close collaboration with business teams to identify data, processing, and visualization needs, allowing us to define priorities and solutions for optimal data management.- **Design and implementation of a Data Lake infrastructure on AWS**:
Creation of an S3 Data Lake to centralize, store, and organize all data from M6's systems. This was to efficiently retrieve data and make it available to various teams (analysis, development, AI).- **Implementation of ETL pipelines with Airflow**:
Development and automation of ETL pipelines orchestrated via Airflow to clean, enrich, and transform data. The use of Spark and Pandas enabled processing of large data volumes and preparation for maximum value extraction.*Deployment of visualization tools:Integration and deployment of suitable visualization tools to allow teams to track key metrics and explore data intuitively.Technical Environment:- **Tools & Technologies**: Kubernetes, GitLab, GitLabCI, Airflow
- **Languages**: Terraform, Python (Pandas & Pyspark)
- **AWS Cloud**: VPC, Route53, S3, EC2, Lambda, EMR, Glue, Redshift, Athena
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Education
- CERTIFICATE 42 IN DIGITAL TECHNOLOGY ARCHITECTURE, Programming / IT developer, general422019CERTIFICAT 42 D'ARCHITECTE EN TECHNOLOGIE NUMERIQUE, Programmation / développeur informatique, général
Certifications
- AWS Certified DevOps Engineer - ProfessionalAWS
- AWS Certified Solutions Architect – ProfessionalAWS