Role Description Configure/maintain/apply security patches to the infrastructure on which the data platform is based, ensure the deployment and the CI/CD of the data or ML delivery. Monitor the performance of the data pipeline and/or the ML models.
Role Description
Configure/maintain/apply security patches to the infrastructure on which the data platform is based, ensure the deployment and the CI/CD of the data or ML delivery. Monitor the performance of the data pipeline and/or the ML models.
Key Objectives
This is you!
Configure/maintain/apply security patches to the infrastructure on which the data platform is based, ensure the deployment and the CI/CD of the data or ML delivery. Monitor the performance of the data pipeline and/or the ML models.
Key Objectives
- Install our tools needed to access our data and manipulate it
- Implement and configure the tools applying the Companies guidelines
- Apply security patches to the different infrastructural components
- analyze and apply if it’s possible the FinOps rules to the different infrastructural components for saving costs purposes
- Configure and maintain the different DBs engine we have on AWS (rds, redshift, postgres standalone installation) something like a DBA
- Work with the Data Architect to ensure development is aligned with the target architecture.
- Develop, Deploy & Maintain the pipelines used in the Data Platform and the local accounts (CT, LO & AS) .
- Operationalize the ML models within the Data Platform.
- Maintain and monitor the different environments for each country (CT, LO & AS)
- Configure networking rules on aws account (NACLs, Route table, security groups)
- Execute Disaster Recovery Test to ensure the data availability in case of Real Disaster
- Support the Developers and Architecture communities analyzing and fixing issue on the different layers on Data Foundation Train and local Teams (CT, LO & AS)
- Maintain an agile mindset every day.
- Interact with security, networking and platform teams to have a secure infrastructure and guarantee a stable environment to the stakeholders
- deployment of the pipeline to ensure high quality and efficiency of the release process and also in the production environment.
- work closely with the Data Architect to monitor the target architecture.
- Communicate with Scrum Master to escalate impediments or improvement for the wagon.
- They work closely with the MLops Devs and data scientists to operationalize the ML models within the Data Platform.
- work closely with the Product Owner and Scrum Master to execute the task assigned to achieve the goal of the wagon.
- Participate in team and train ceremonies: PI planning, Sprint planning, Retrospectives, Daily scrum or stand up meetings.
This is you!
- You are enthusiasm to work in an European team to develop the technical capabilities in a common European Data Platform
- Have an Agile mind-set and you are open to new ideas and creative ways to work
- You are organized and get things done!
- Must have:
- Kubernetes, Spark, PySpark, Python, SQL, Docker, Git, Gitflow
- AWS Cloud Services (EKS, EC2, S3, VPC, RDS, IAM, SQS, SNS, ECS, ECR, API Gateway, CloudWatch, RedShift, Glue, Athena, GuardDuty, Air Flow...)
- IaC : Cloudformation, CDK,Terraform
- DB engine(SQL/NO-SQL): Oracle, Postgres, SQL Server, Redshift, Aurora, Dynamo
- Nice to have:
- Data warehouses modeling/ DBA
- Jupyter Notebook, pip, R, Java
- BI tools: Microstrategy, Quicksight,Tableau
- ETL/ELT: SAS serves configuration, Talend, Glue
- Data Virtualization tool: Denodo, Denodo MPP
- Data Quality tools: Collibra DQ, Collibra data platform
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