Cyril Fait
Lead Cloud Data Platform Engineer - ED
Greater Paris Metropolitan Region France
Summary
🤩
RockstarCyril Fait is a Lead Cloud Data Platform Engineer based in the Greater Paris area with a strong track record building production-grade cloud and data platforms over the past decade and four years in senior cloud roles. He combines hands-on IaC, DevOps and data engineering expertise—having architected landing zones, serverless data lakes and global datacenter migrations for enterprise clients while mentoring teams on Kubernetes, security and cost optimisation. At AWS he contributed to aws-sdk-pandas and serverless data lake frameworks, improving build/test infra and Lambda layer support across Python versions and architectures for a widely used open-source project. Cyril is comfortable operating across Python, TypeScript and Terraform/CDK, and has repeatedly modernised CI/CD and test pipelines for data platforms. He brings a pragmatic focus on deployability and observability, with experience delivering high-traffic container platforms (including FIFA-level scale) and automated user provisioning across multi-account AWS estates. Notably, he blends deep infrastructure automation skills with practical data engineering sensibilities, making him adept at moving analytics projects from prototype to resilient production.
4 years of coding experience
12 years of employment as a software developer
English
Github Skills (34)
docker10
aws-cdk10
python10
data-engineering10
aws-lambda10
cloud-infrastructure10
dockers10
cicd10
aws10
aac10
build-automation10
infrastructure-as-code10
cloud-services10
data-lake10
devops10
Programming languages (2)
Github contributions (5)
aws-solutions-library-samples/data-lakes-on-aws
Dec 2022 - Jan 2023
Enterprise-grade, production-hardened, serverless data lake on AWS
Role in this project:
DevOps Engineer & Data Engineer
DevOps Engineer & Data EngineerContributions:36 releases, 10 reviews, 27 commits in 1 month
Contributions summary:Cyril primarily contributed to improving the CI/CD pipeline and data engineering aspects of the project. They updated build scripts for Python Lambda layers and AWS CodeBuild runtimes to use Python 3.9, reflecting a focus on infrastructure and deployment. The user also updated dependencies and configurations related to data quality, including integrating tools like `validate.sh`. Moreover, there's evidence of updates to deploy scripts and dependencies for the data lake.
serverlessproduction-gradedata-lakeawsiac
aws/aws-sdk-pandas
Feb 2022 - Dec 2022
pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, Neptune, OpenSearch, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).
Role in this project:DevOps Engineer & Cloud Engineer
DevOps Engineer & Cloud EngineerContributions:1 release, 38 reviews, 41 commits in 10 months
Contributions summary:Cyril primarily focused on enhancing the build process and infrastructure for the AWS Data Wrangler project. They implemented support for building Lambda layers for different Python versions (3.9, 3.8, 3.7, and 3.6) and architectures (aarch64), utilizing Amazon Lambda base images. The user also added test infrastructure for various databases like Oracle and Redshift Serverless. They also migrated the test infrastructure from CDK v1 to v2 and updated OpenSearch test instances.
amazon-sagemaker-notebookcsvpythonsqlserverpolars
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.