ETL Data Engineering Practitioner with AWS

An international project focused on designing and developing scalable data engineering solutions and cloud-based data platforms using technologies such as AWS, Python, SQL, Apache Spark, and distributed data processing.

• 5+ years of professional experience in Data Engineering.
• Strong hands-on experience with AWS and cloud-based data platforms.
• Excellent knowledge of Python and SQL.
• Solid experience with ETL/ELT processes and data integration.
• Experience with Big Data technologies and distributed systems.
• Experience designing scalable Data Warehouses and/or Data Lakes.
• Strong database knowledge and experience with database performance optimization.
• Understanding of data architecture, scalability, resilience, and security.
• Ability to troubleshoot complex technical and performance-related issues.
• Experience taking technical ownership and influencing architectural decisions.
• Good communication skills and ability to collaborate with technical and business stakeholders.
• Experience mentoring other engineers or acting as a technical lead is an advantage.
• Experience with Scrum Master responsibilities is a plus.

• Design and implement scalable data engineering solutions and data architectures.
• Develop and optimize advanced ETL/ELT pipelines and data processing workflows.
• Work with large-scale data processing using AWS and Big Data technologies.
• Design and maintain Data Warehouses, Data Lakes, and data processing frameworks.
• Troubleshoot complex performance and scalability issues across data platforms.
• Work with relational databases and optimize database performance.
• Ensure data platforms are scalable, secure, resilient, and reliable.
• Contribute to data architecture standards, best practices, and technical decisions.
• Collaborate with technical teams and business stakeholders to translate requirements into effective data solutions.
• Contribute to data governance and continuous improvement of data infrastructure.
• Support and mentor less experienced Data Engineers and contribute to technical knowledge sharing.
• Participate in architectural discussions to help shape the long-term direction of the data platform.