Data Engineer

About the role

We are looking for a Data Engineer to design, develop, and maintain robust data solutions that support data generation, collection, and processing across the organization. The role involves building data pipelines, ensuring data quality, and implementing ETL processes to move data efficiently between systems.

Key responsibilities

• Design and develop scalable data pipelines using PySpark.
• Implement and manage ETL processes for data migration and deployment.
• Ensure data quality and consistency throughout the data lifecycle.
• Optimize data processing workflows for performance and cost efficiency.
• Collaborate with cross‑functional teams to gather requirements and deliver tailored data solutions.
• Participate actively in team discussions and act as a subject‑matter expert.

Required profile

• Minimum 5 years of professional experience in data engineering.
• Strong understanding of data modeling and database design principles.
• Experience with cloud platforms and services for data storage and processing.
• Ability to work independently and contribute to team problem‑solving.

Required skills

• Proficiency in PySpark.
• Experience with ETL tools and data integration techniques.
• Knowledge of data quality frameworks and best practices.
• Familiarity with cloud platforms (e.g., AWS, Azure, GCP).
• Understanding of data modeling and database design.