Context and problematic

In regard to the creation of a new entity of a major player in the banking sector, we are in charge of the development of the Data and Analytics section of the IS. The latter should allow customers to view services, prices and then subscribe online.

Last but not least, a credit application scoring shall will be developed to automatically grant or refuse a request.

Goals

Implementation and design of Datalake and DataWareHouse.
Ingestion and pre-cleaning of data providers while industrializing pricing models.
Allow businesses and customers to view their pricing in real time but mostly credit requests

Our intervention

1 Data Architect, 2 Data Engineers, 1 full-stack developer

• Implementation and design of Datalake and DataWareHouse
• Ingestion and pre-cleaning of data providers while industrializing pricing models.
• Allow businesses and customers to view their pricing in real time and mostly credit requests
• Putting pricing models into production

Results

Platform is functional since December 2019 for the business across all structures worldwide

Several streaming and batch ingestion pipelines in production

During the industrialization phase for the customer

Technical environment

Python, Go, Typescript, vue.JS, Node.JS
AWS: S3, VPC, IAM, Cognito, ECS/ECR, Lambda, Glue, RDS, Fargate, Batch, WAF, API Gateway, DynamoDB, ElasticCache, Route53, EventBridge, SageMaker
Elastic Search, Kibana
Docker, Kubernetes, Terraform