Lead, Data And Ai Engineer - Schneider Electric

OverviewIn 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 / Beneficioshybrid work planflexible scheduleFloating HolidaysHoly Pack (additional vacation days)Sabbatical Pack (up to 2 months unpaid leave)Wellbeing platforms (Wellwo/Wellhub)ResponsabilidadesDesign, build, and maintain scalable data pipelines and data platforms on AWSDevelop cloud-native data solutions using S3, Lambda, Glue, RDS, Step Functions, and IAMImplement Infrastructure as Code with AWS CloudFormation for repeatable deploymentsBuild and maintain CI/CD pipelines with GitHub Actions and CloudFormationWrite production-grade code in Python or Node.jsSupport post-deployment/production operations including troubleshooting and performance tuningCollaborate with solution architects and engineers to improve architecturesCollaborate with Data Scientists, AI Engineers, and stakeholders to enable scalable AI/ML workloadsEnsure security, scalability, reliability, and cost optimizationWork in an Agile delivery model and participate in code reviews and continuous improvement initiativesRequisitos principales5-8 years as a Data Engineer in AWS-based environmentsStrong hands-on AWS experience (S3, Lambda, IAM, RDS, Glue, Step Functions)Proven CI/CD experience using GitHub ActionsSolid Infrastructure as Code experience, preferably CloudFormationStrong Python or Node.js programming skillsProduction support experience in live environmentsFamiliarity with Agile/ScrumUnderstanding of data modeling, governance, quality, metadata, and master data conceptsExperience with structured and unstructured data for AI/analyticsFamiliarity with data lake architectures, Lakehouse concepts, and modern data platformsExposure to AI security, responsible AI, and data privacy principlesProactive, self-driven mindsetStrong problem-solving abilitiesEffective cross-functional collaborationAWS core services: S3, Lambda, IAM, RDS, Glue, Step FunctionsGitHub Actions for CI/CDInfrastructure as Code with CloudFormation

Requisitos principales5-8 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 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 principles Proactive, self-driven mindset Strong problem-solving abilities Effective cross-functional collaboration AWS core services: S3, Lambda, IAM, RDS, Glue, Step Functions GitHub Actions for CI/CD Infrastructure as Code with CloudFormation