ETL Data Engineering Practitioner with AWS

• 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.
• Experience designing and implementing complex data engineering solutions.
• 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 the ability to collaborate with both technical and business stakeholders.
• Experience mentoring other engineers or acting as a technical lead will be 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 other technical teams and business stakeholders to understand requirements and translate them into effective data solutions., Contribute to data governance and the continuous improvement of the organization's data infrastructure., Support and mentor less experienced Data Engineers and contribute to technical knowledge sharing., Participate in architectural discussions and help shape the long-term direction of the data platform.] Requirements: Data, AWS, Python, SQL, ETL, ELT, Big data, Distributed systems, Data warehouses, Data Lake, Communication skills, Stakeholder management Additionally: Sport subscription, Private healthcare.