Data Engineer – Schneider Digital, part of Schneider Electric.ResponsibilitiesPlay an instrumental role in the design, development, and maintenance of new ETL, data extractions and ingestions, and data quality, ensuring FAIR principles are achieved.Work with large and complex datasets within the platform and make them available to different stakeholders.Define and build scalable data pipelines to integrate and model datasets from complex data sources.Ensure quality best practices, defining and implementing automated testing of data pipelines and orchestration.Collaborate with data team members to define data quality rules and KPIs for monitoring and exception alerts.Diagnose and triage infrastructure problems and outages related to the data & analytics platform.Learn fast about new technologies; the project is growing fast and will soon serve other business units, requiring continuous learning.Closely collaborate with our cloud engineering team to drive automation and observability as key success factors.QualificationsA bachelor’s degree in Computer Science, Engineering, Mathematics, Economics, or a related field.Minimum of 2 years’ experience in a data engineering role.Familiarity with data processing concepts such as ETL/ELT pipelines.Experience with Python and Git.Knowledge of good practices for Python development (project structure, testing, formatting, deployment).Hands‑on experience building with PySpark.Experience with S3 for object storage and data lakes.Experience in data modeling.Experience in developing and operating workflow orchestration.Understanding of data partitioning and file formats like Iceberg and Delta.Understanding of data warehousing concepts and querying languages such as SQL.Agile knowledge.Fluency in English.Desirable Skills/ExperienceExperience with EMR, Databricks and AWS Glue.Familiarity with the AWS console and basic command‑line tools (AWS CLI).Basic understanding of AWS serverless services such as Lambda, Step Functions, AW