Lead, Data and AI Engineer

At Schneider Electric, we are the leading digital partner in sustainability and efficiency for businesses, communities, and individuals. Our goal is for all people to be able to make the most of our energy and resources through the integration of processes, software, big data, and energy technologies that enable integrated management of buildings, industries, and cities. We are present in over 110 countries with a diverse and disruptive team of over 150,000 people.

If you are seeking an opportunity to propel your career and challenge your creativity, we want to meet you!

Schneider Digital is the digital department of Schneider Electric, leading the digital transformation in the company by giving support globally to our internal teams and our clients. Schneider Digital consists of 6 Digital Hubs worldwide which are strategically located to ensure a 24/7 support across the company (France, China, India, USA, Mexico and Spain).

We are looking for a hands‑on Data Engineer with strong AI experience to design, develop, deploy, and support scalable, cloud‑native data solutions. This role will work closely with product, architecture, Dev Ops, and analytics teams to deliver reliable and secure data platforms, while providing post‑production support for live systems. The ideal candidate brings deep technical expertise, a proactive mindset, and a passion for building high‑quality data solutions in a fast‑paced Agile environment.

• Design, build, and maintain scalable data pipelines and data platforms using AWS services.
• Develop and manage cloud-native data solutions leveraging services such as S3, Lambda, Glue, RDS, Step Functions, and IAM.
• Implement Infrastructure as Code (IaC) using AWS Cloud Formation to ensure repeatable and reliable deployments.
• Build and maintain CI/CD pipelines using Git Hub Actions integrated with Cloud Formation.
• Write production‑grade, maintainable code using Python or Node.js.
• Support post‑deployment and production (PROD) operations, including troubleshooting, incident resolution, and performance tuning.
• Collaborate with solution architects and engineers to contribute to solution design and continuously improve existing architectures.
• Collaborate with Data Scientists, AI Engineers, and business stakeholders to enable scalable and secure AI/ML workloads.
• Ensure best practices for security, scalability, reliability, and cost optimization are followed.
• Work in an Agile delivery model, adapting to evolving business requirements and priorities.
• Participate in code reviews, technical discussions, and continuous improvement initiatives.

• 5–8 years of experience working as a Data Engineer in AWS-based environments.
• Strong hands‑on experience with core AWS services, including: S3, Lambda, IAM, RDS, Glue, Step Functions.
• Proven experience in defining and managing CI/CD workflows using Git Hub Actions.
• Solid experience with Infrastructure as Code, preferably AWS Cloud Formation.
• Strong programming skills in Python or Node.js.
• Experience supporting production systems and handling operational issues in live environments.
• Familiarity with Agile/Scrum delivery practices.
• Strong understanding of data modeling, data governance, data quality, metadata management, and master data concepts.
• Experience working with structured and unstructured data to support AI and analytics use cases.
• 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 with strong problem‑solving abilities.
• Ability to work effectively with cross‑functional teams including product, architecture, and Dev…