Senior Data Engineer (AWS Redshift/PySpark)

Role: Data Engineer

Job Type: Permanent - Hybrid

Location: Budapest, HU

What You Will Do:

• Design, build, and maintain robust data pipelines that are scalable, efficient, and meet business needs
• Collaborate with cross-functional teams to understand and translate business requirements into data solutions
• Ensure data quality, integrity, and governance by implementing best practices in data management
• Develop ETL processes and data flows
• Support and enhance data platforms, databases, and data warehouses to enable advanced analytics
• Implement CI/CD pipelines using GitHub Actions and JFrog for automated deployment and version control
• Troubleshoot data pipelines and address any issues with real-time, batch data processing, and integrations

What You Will Bring:

• 5+ years of experience in data engineering
• Experience with cloud data warehouse environments
• Experience with AWS Redshift
• Hands-on experience with PySpark and Apache Airflow
• Strong SQL skills and deep understanding of query performance tuning in Redshift
• Solid understanding of data modeling principles, including dimensional modeling (Kimball), normalized models, and hybrid strategies
• Experience with monitoring tools (CloudWatch, Redshift Console)
• Familiarity with data versioning, CI/CD, and collaborative development practices in dbt

… and we appreciate if you have:

• Experience in Airflow, AWS Glue

Please email me "[email protected]" with your updated CV, I will contact you at the earliest.