MLOps Engineer

About the job 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 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) Main Responsibilities 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. Requirements: 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