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Senior Data Engineer - AWS REDSHIFT/PYSPARK (JT)

Discussion
  • 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
  • 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
  • Confident English
  • Candidate needs to be to be currently eligible to work in Hungary.
  • Experience in Airflow, AWS Glue
  • hybrid work (2 day/office)
  • competitive salary

See also

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