Lead, Data And Ai Engineer

Experteer Overview Lea el resumen de esta oportunidad para comprender qué habilidades, incluidas las habilidades interpersonales relevantes y el dominio de paquetes de software, se requieren.In this hands-on Data Engineer role within Schneider Digital, you design, build, and operate scalable, cloud-native data platforms on AWS to support AI/ML workloads and business analytics.You collaborate with product, architecture, DevOps, and data teams to deliver secure, reliable data solutions while supporting live systems.You’ll work in an Agile environment, driving best practices in security, scalability, and cost optimization to enable data-driven decisions across the organization.Compensaciones / Beneficios* Design, build, and maintain scalable data pipelines and data platforms on AWS* Develop cloud-native data solutions using S3, Lambda, Glue, RDS, Step Functions, and IAM* Implement Infrastructure as Code with AWS CloudFormation for repeatable deployments* Build and maintain CI/CD pipelines with GitHub Actions and CloudFormation* Write production-grade code in Python or Node.js* Support post-deployment/production operations including troubleshooting and performance tuning* Collaborate with solution architects and engineers to improve architectures* Collaborate with Data Scientists, AI Engineers, and stakeholders to enable scalable AI/ML workloads* Ensure security, scalability, reliability, and cost optimization* Work in an Agile delivery model and participate in code reviews and continuous improvement initiativesResponsabilidades* 5-8 years as a Data Engineer in AWS-based environments* Strong hands-on AWS experience (S3, Lambda, IAM, RDS, Glue, Step Functions)* Proven CI/CD experience using GitHub Actions* Solid Infrastructure as Code experience, preferably CloudFormation* Strong Python or Node.js programming skills* Production support experience in live environments xqbhyrx * Familiarity with Agile/Scrum* Understanding of data modeling, governance, quality, metadata, and master data concepts* Experience with structured and unstructured data for AI/analytics* Familiarity with data lake architectures, Lakehouse concepts, and modern data platforms* Exposure to AI security, responsible AI, and data privacy principlesRequisitos principales* hybrid work plan* flexible schedule* Floating Holidays* Holy Pack (additional vacation days)* Sabbatical Pack (up to 2 months unpaid leave)* Wellbeing platforms (Wellwo/Wellhub)

You’ll work in an Agile environment, driving best practices in security, scalability, and cost optimization to enable data-driven decisions across the organization.Compensaciones / Beneficios* Design, build, and maintain scalable data pipelines and data platforms on AWS* Develop cloud-native data solutions using S3, Lambda, Glue, RDS, Step Functions, and IAM* Implement Infrastructure as Code with AWS CloudFormation for repeatable deployments* Build and maintain CI/CD pipelines with GitHub Actions and CloudFormation* Write production-grade code in Python or Node.js* Support post-deployment/production operations including troubleshooting and performance tuning* Collaborate with solution architects and engineers to improve architectures* Collaborate with Data Scientists, AI Engineers, and stakeholders to enable scalable AI/ML workloads* Ensure security, scalability, reliability, and cost optimization* Work in an Agile delivery model and participate in code reviews and continuous improvement initiativesResponsabilidades* 5-8 years as a Data Engineer in AWS-based environments* Strong hands-on AWS experience (S3, Lambda, IAM, RDS, Glue, Step Functions)* Proven CI/CD experience using GitHub Actions* Solid Infrastructure as Code experience, preferably CloudFormation* Strong Python or Node.js programming skills* Production support experience in live environments xqbhyrx * Familiarity with Agile/Scrum* Understanding of data modeling, governance, quality, metadata, and master data concepts* Experience with structured and unstructured data for AI/analytics* Familiarity with data lake architectures, Lakehouse concepts, and modern data platforms* Exposure to AI security, responsible AI, and data privacy principlesRequisitos principales* hybrid work plan* flexible schedule* Floating Holidays* Holy Pack (additional vacation days)* Sabbatical Pack (up to 2 months unpaid leave)* Wellbeing platforms (Wellwo/Wellhub)