ETL Data Engineering Practitioner
Nasze wymagania:
- 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.
Mile widziane:
- Experience mentoring other engineers or acting as a technical lead.
- Experience with Scrum Master responsibilities.
O projekcie:
We are looking for an experienced Data Engineer to join an international project focused on designing and developing scalable data engineering solutions and cloud-based data platforms. You will work on complex data processing and integration solutions, with a strong focus on AWS, ETL/ELT, distributed data processing, databases and data architecture. The role combines hands-on engineering with technical ownership, architecture and mentoring responsibilities.
Zakres obowiązków:
- 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.