Industry 4.0 Data Engineer

About the role

As a Data Engineer, you will work with cross‑functional stakeholders to understand operational use cases and deliver data solutions that support business decision‑making. You will be responsible for developing data pipelines, ensuring their security, reliability, and efficiency, as well as designing and maintaining scalable datasets for analytics and reporting.

Key responsibilities

• Design, develop, and maintain data pipelines and ingestion processes to integrate data from multiple enterprise systems.
• Ensure reliability, efficiency, and performance of data pipelines and platform components.
• Develop and maintain well‑structured datasets, contributing to metadata management and semantic modelling.
• Maintain data quality, lineage, and observability to ensure trusted, traceable datasets.
• Manage changes to data structures and pipelines, including schema evolution and refactoring.
• Apply data security, access control, and compliance standards for sensitive data.
• Collaborate with SMEs, analysts, and business users to understand requirements and support data governance.
• Provide documentation, knowledge sharing, and day‑to‑day support for data products.

Required profile

• Master’s degree in computer science, data science, or a related technical field.
• 2‑5 years of experience in data engineering, data platform development, or ETL pipeline development.
• Strong experience with Python and SQL, and exposure to distributed processing frameworks such as Spark.
• Proven experience building data pipelines and ETL processes from disparate sources.
• Experience working in a multinational organization with cross‑functional teams.
• Experience with relational and large‑scale datasets in enterprise environments.
• Experience working in Agile environments.
• Effective communication skills in English, both spoken and written.

Required skills

• Python
• SQL
• Apache Spark
• ETL development
• Data pipeline design