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Data Science Engineer
Il y a 2 mois
Schneider Electric is a global leader in energy management and automation. Our purpose is to empower all to make the most of our energy and resources, bridging progress and sustainability for all.
Job DescriptionWe are seeking a Senior Data Engineer to contribute to the design, development, and deployment of Advanced Data Processing applications within Schneider Electric product and service offers in the Energy Management and Industrial Automation domains.
Responsibilities:- Analyze complex data processing use cases and corresponding data.
- Specify, design, implement, test, validate, and industrialize advanced data management functions to be incorporated in products, systems, and solutions.
- Contribute to state-of-the-art monitoring, technological watch, and experimentation of new technologies, tools, and processes, to improve products and services as well as development practices within the company.
- Identify and evaluate potential external partners.
- Contribute to intellectual property protection, capitalization of knowledge, and internal and external communication.
- Master or PhD or equivalent diploma in Computer Science with a minimum of 2-3 years of experience in Data Engineering (Processing, Pipelines, etc).
- Python, Spark, PySpark, SQL/NoSQL, ETL/ELT skills.
- Experience with public cloud services: Microsoft Azure and/or AWS.
- Knowledge of technologies such as Databricks, Kubernetes, Docker, OpenDataSoft would be an asset.
- AI exposure (Data Science, Machine Learning, MLOps) and Big Data / Data Analysis / Data Visualization background would be an asset.
- Capacity to perform coding, debugging, testing (including unit tests, functional tests, and integration tests) and troubleshooting throughout the application development process and in agile mode.
- Knowledge of other programming languages would be an asset: Java, C++, C#, JavaScript, R, Matlab.
- Ideally, some knowledge of Energy Management and Automation markets.
- Orientation towards solving problems, achieving results, and applying technology to real-life business cases.
- Effective communication skills including aptitude for data-driven storytelling: convincing with words, impacting with data, and influencing with visuals.
- Autonomy and capacity to cooperate.
- Openness of mind and scientific rigor.
- Fluent in English.
