At Schneider Electric, we are committed to solving real-world problems to create a sustainable, digitized, new electric future.

Artificial Intelligence has the potential to transform industries and help unlock efficiency and sustainability.

Within our Global AI Hub we combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization.

Your role : As part of the AI Technology group (70 people), we are seeking an experienced cloud data Ops engineer who can contribute to the development of our AI platform, which is used by our internal stakeholders to design and deploy AI use cases for our external offers and internal functions.

We look for someone with a data engineering background and with strong experience on cloud platforms, specifically on AWS cloud.

He/she must be passionate about solving complex business & technical problems by applying best in class engineering, quality, and security practices in the context of Data & AI software developments & integration.

Our AI platform is built on top of Databricks and Azure & AWS cloud providers.

Your responsibilities :

About the delivery of new data oriented features in the AI platform:

Contribute to the identification and evaluation of potential external partners & tools Contribute, potentially in collaboration with internal stakeholders, to design of new data oriented features of the AI Platform Collaborate with data and domain experts to identify data transformation methods, tools and technologies to build platform & product offerings Collaborate with other AI Technology teams, understand their challenges and make opinionated recommendations that empower them with data solutions Implement data observability and monitor data pipelines in production to ensure proper operations Write infrastructure as code and CI/CD workflows to deploy the data cloud infrastructure Contribute, from ideation up to industrialization, to the development of re-usable, data-oriented components, libraries or functions

About the support of internal stakeholders:

Engineer efficient, scalable, and adaptable data pipelines to process structured, semi structured and unstructured data Maintain and rethink existing datasets and pipelines to service a large variety of use cases Occasionally be embarked into an internal stakeholders teams to bring support & expertise on the data features of the AI platform and, in return, collect platform evolution needs Occasionally contribute to the collective effort of run & support for the AI Platform Other responsibilities: Contribute to intellectual property protection, capitalization of knowledge, and internal and external communication Contribute to the technical watch on data topics Your profile : Master or PhD or equivalent diploma in Data Processing, computer science, with a minimum of 5 years of experience Expert in engineering data pipeline using technologies such as Presto, Spark or Flink and or the equivalent managed services from public cloud providers Experienced with Azure/AWS public cloud infrastructure (AWS preferred) and Databricks Experienced with Python, Spark and DevOps technologies (Kubernetes, Docker, Github actions, Terraform) Fluent English At ease in an international work environment Eager to take on the responsibility and the supervision of end-to-end delivery of new data oriented features Ideally, some knowledge of Energy Management and Industrial Automation markets.

Software engineering skills/experience: capacity to perform coding, coding review, debugging, testing (including unit tests, functional tests, and integration tests) and troubleshooting throughout the application development process and in agile mode.

Orientation towards solving problems, achieving results, and applying technology to real-life business cases.

Effective communication skills including aptitude for data-driven story telling: convincing with words, impacting with data, and influencing with visuals.

Strong inclination towards coaching, supporting and assisting other team members Autonomous AND capacity to cooperate.

Open minded AND rigorous Looking to make an IMPACT with your career?

When you are thinking about joining a new team, culture matters.

At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success.

We believe that our IMPACT values – Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork – starts with us. IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play.

It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world.

We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization.

We celebrate IMPACT Makers and believe everyone has the potential to be one.

Become an IMPACT Maker with Schneider Electric – apply today! €36 billion global revenue +13% organic growth 150 000+ employees in 100+ countries #1 on the Global 100 World’s most sustainable corporations You must submit an online application to be considered for any position with us.

This position will be posted until filled.

Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best.

We mirror the diversity of the communities in which we operate, and ‘inclusion’ is one of our core values.

We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do.

At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value.

Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders.

You can find out more about our Trust Charter here Schneider Electric is an Equal Opportunity Employer.

It is our policy to provide equal employment and advancement opportunities in the areas of recruiting, hiring, training, transferring, and promoting all qualified individuals regardless of race, religion, color, gender, disability, national origin, ancestry, age, military status, sexual orientation, marital status, or any other legally protected characteristic or conduct.

At Schneider Electric, we are committed to solving real-world problems to create a sustainable, digitized, new electric future.

Artificial Intelligence has the potential to transform industries and help unlock efficiency and sustainability.

Within our Global AI Hub we combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization.

Your role : As part of the AI Technology group (70 people), we are seeking an experienced cloud data Ops engineer who can contribute to the development of our AI platform, which is used by our internal stakeholders to design and deploy AI use cases for our external offers and internal functions.

We look for someone with a data engineering background and with strong experience on cloud platforms, specifically on AWS cloud.

He/she must be passionate about solving complex business & technical problems by applying best in class engineering, quality, and security practices in the context of Data & AI software developments & integration.

Our AI platform is built on top of Databricks and Azure & AWS cloud providers.

Your responsibilities :

About the delivery of new data oriented features in the AI platform:

Contribute to the identification and evaluation of potential external partners & tools Contribute, potentially in collaboration with internal stakeholders, to design of new data oriented features of the AI Platform Collaborate with data and domain experts to identify data transformation methods, tools and technologies to build platform & product offerings Collaborate with other AI Technology teams, understand their challenges and make opinionated recommendations that empower them with data solutions Implement data observability and monitor data pipelines in production to ensure proper operations Write infrastructure as code and CI/CD workflows to deploy the data cloud infrastructure Contribute, from ideation up to industrialization, to the development of re-usable, data-oriented components, libraries or functions

About the support of internal stakeholders:

Engineer efficient, scalable, and adaptable data pipelines to process structured, semi structured and unstructured data Maintain and rethink existing datasets and pipelines to service a large variety of use cases Occasionally be embarked into an internal stakeholders teams to bring support & expertise on the data features of the AI platform and, in return, collect platform evolution needs Occasionally contribute to the collective effort of run & support for the AI Platform Other responsibilities: Contribute to intellectual property protection, capitalization of knowledge, and internal and external communication Contribute to the technical watch on data topics
Your profile : Master or PhD or equivalent diploma in Data Processing, computer science, with a minimum of 5 years of experience Expert in engineering data pipeline using technologies such as Presto, Spark or Flink and or the equivalent managed services from public cloud providers Experienced with Azure/AWS public cloud infrastructure (AWS preferred) and Databricks Experienced with Python, Spark and DevOps technologies (Kubernetes, Docker, Github actions, Terraform) Fluent English At ease in an international work environment Eager to take on the responsibility and the supervision of end-to-end delivery of new data oriented features Ideally, some knowledge of Energy Management and Industrial Automation markets.

Software engineering skills/experience: capacity to perform coding, coding review, debugging, testing (including unit tests, functional tests, and integration tests) and troubleshooting throughout the application development process and in agile mode.

Orientation towards solving problems, achieving results, and applying technology to real-life business cases.

Effective communication skills including aptitude for data-driven story telling: convincing with words, impacting with data, and influencing with visuals.

Strong inclination towards coaching, supporting and assisting other team members Autonomous AND capacity to cooperate.

Open minded AND rigorous