Freelancer profile translated to English.

Description

Looking for a data expert to design, optimize, and industrialize your cloud architectures with modern technologies likeDatabricks**, **Apache Spark**, **Snowflake**, and **AWSto leverage your data and accelerate your analytical projects?

As a **Senior Data Engineer**, I will guide you from design to production:

Architecture of cloud data platforms based on AWS, GCP, and Azure

Implementation of high-performance data pipelines withDatabricksandApache Spark

Adoption ofDataOpspractices to automate and ensure the reliability of your workflows

Cost and performance optimizationof yourCloud**, **Databricks**, and **Snowflakeenvironments

I am a senior Data Engineer with over 10 years of experience in large-scale data processing and cloud solution industrialization. I have led data projects integratingAWS**, **Databricks**, **Apache Spark**, **Snowflake**, and **DataOpsapproaches, servingbusiness performanceand **data governance**.

Industry field of expertise

Languages

French
Native or bilingual
English
Conversational

Workplace preferences

Can work on-site

Paris (up to 50km), Paris (up to 100km)

CNP Assurances
Senior Data Engineer Databricks | AWS | Apache Spark | Snowflake | DataOps
BANKING AND INSURANCE
August 2024 - Today (1 year and 10 months)
Paris, France
Context: As part of my clients' digital transformation, I designed and deployed
advanced data engineering and cloud automation solutions to modernize and
industrialize business data management.
— Design and implementation of reusable components for a scalable Data
Mesh platform on AWS (IAM, S3, Lambda, Glue), Databricks (Unity Catalog, Delta Sha-
ring, Workflows), and Terraform for data domain provisioning automation.
— Implementation of a serverless architecture (AWS Lambda, Step Functions, EventBridge)
orchestrating business data flows and facilitating their integration into Snowflake.
— Snowflake pipeline optimization: Implementation and management of data flows
to ensure efficient and scalable ingestion.
— Development of ELT workflows on Snowflake, optimizing flows to reduce costs
and improve analytical query performance.
— Creation of ingestion, onboarding, and CI/CD orchestration frameworks (GitLab
CI, Azure DevOps), accelerating deployment speed and product team autonomy.
— Industrialization of cloud deployments via AWS CloudFormation and Terra-
form scripts, reducing provisioning time by 70 percent.
— Development of pipelines in Apache Spark Structured Streaming (Databricks, Delta
Lake) with advanced error handling and performance optimization.
— Construction of observability dashboards in Datadog for monitoring workloads
and production platform health.
— Consulting and support for data teams in platform adoption, as well as
model design (Star Schema, Data Vault), writing architecture documentation
and infrastructure cost estimations.
$

AWS Lambda, Step Functions, Databricks, Terraform, Gitlab CI, AWS, Snowflake, Infor-
matica, CloudFormation, Azure DevOps, CI/CD, serverless architecture, data pipeline optimization.
Terraform CloudFormation Spark Databricks Snowflake
SNCF Connect
Senior Data Engineer Databricks | AWS | Kafka | FinOps | DataOps
TRANSPORTATION
August 2021 - August 2024 (3 years)
France, France
• Led the migration of data systems to AWS, optimizing processing pipelines for a daily volume of 6 TB.

• Implemented advanced cost reduction strategies, decreasing cloud expenses by 30% while improving performance.

• Developed optimized AWS Lambda functions for automating data management processes.

• Automated the deployment of complex stacks using Terraform and CloudFormation, reducing provisioning time by 50%.

• Managed operations (RUN) and on-call duties, ensuring continuous availability and compliance with security standards.

Technical Environment: AWS (Glue, Lambda, Step Functions, Kinesis, EMR, Redshift, S3, Terraform, CloudFormation, IAM, CloudTrail, Config, MSK), Python, Kafka, Ansible, Git, Jenkins, Docker, PyCharm.
Lambda CloudFormation Python Terraform Amazon Web Services
Dalkia
Data Engineer AWS | Spark | Snowflake | Python
TRANSPORTATION
March 2020 - Today (6 years and 3 months)
Courbevoie, France
• Designed a robust AWS Data Lake for real-time data integration and analysis, increasing analysis efficiency by 40%.

• Used AWS Glue and Amazon EMR to develop complex ETL workflows, reducing processing time by 60%.

• Migrated on-premises databases to AWS RDS and Redshift, improving query performance and data management.

• Worked with DevOps teams to enhance the resilience and security of the AWS infrastructure.

Technical Environment: AWS (Glue, EMR, Redshift, RDS, S3, Lambda), Spark, Python, Docker, Git, Jenkins, Terraform.

Amazon Web Services Lambda Spark S3 Python