Data Engineer

About the role

The Data Engineer will design, develop, and manage scalable data pipelines that move data from multiple sources into databases, data lakes, or warehouses. You will ensure data is clean, reliable, and ready for business analysis, working in a hybrid environment that balances autonomy with collaborative support.

Key responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for data collection, transformation, and integration.
• Maintain and optimise databases, data warehouses, and data lakes for integrity, performance, and cost efficiency.
• Integrate data from APIs, cloud storage, third‑party systems, and on‑premise databases.
• Implement data validation, monitoring, and troubleshooting processes.
• Manage cloud infrastructure (AWS, Azure) and automate repetitive tasks using Python and SQL.
• Document data architectures, pipelines, and workflows for the IT department.
• Collaborate with data and business teams to translate requirements into technical solutions.

Required profile

• Bachelor’s degree in Computer Engineering, Data Science, Statistics, Physics or a related IT field.
• Experience working in Agile environments (Scrum or Kanban).
• Proven ability to work with cloud platforms, especially Azure.

Required skills

• Programming: Python, PySpark, SQL, DAX.
• Data formats: Parquet, CSV, XLSX, JSON, TXT.
• Cloud & platforms: Azure, AWS, Databricks, PowerBI, Linux.
• Version control: GitHub.
• ETL/ELT processes and data integration tools.

What we offer

• Hybrid work model with modern open‑floor office spaces.
• Autonomy and freedom to experiment within a well‑governed environment.
• Support from HR, Finance, and IT management adhering to high integrity standards.