Data Engineer (m/f/d)

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• Design, implement, and maintain scalable ETL pipelines using AWS Glue (Spark), Python, and PySpark.
• Manage complex data workflows and dependencies, including with AWS Lambda, using Airflow (or similar orchestration tools).
• Integrate and optimize data flows across various AWS services like S3 (Glue Catalog, Athena), Aurora Postgres, Redshift, and Iceberg tables.

• Proficiency in Python (including Pandas) for data transformations using TDD; hands-on experience with Apache Spark, ideally via AWS Glue
• Experience with AWS services (S3, Glue, Athena, Redshift, Aurora, Lambda, IAM, EventBridge); comfortable with cloud-based architecture, serverless design, and deployment strategies
• Experience in building and managing DAGs in Airflow (or similar tools); familiarity with Lambda-based event-driven architectures
• Proficiency with Git (branching, pull requests, code reviews) and CI/CD pipelines; understanding of release management and automated testing in a multi-environment setup
• Hands-on experience with distributed processing frameworks (like Spark) and large-scale data lake solutions, including Iceberg tables; familiarity with data lake architectures, partitioning strategies, and best practices
• Strong skills in optimizing Spark jobs and SQL queries for performance
• Knowledge of data security practices, including encryption, access controls, and compliance in cloud environments
• SQL knowledge for properly designing and maintaining data schemas for efficient querying and reporting is an advantage
• Familiarity with tools like Terraform or CloudFormation for automated AWS provisioning is an advantage
• Experience with event-driven architectures and working with AWS EventBridge / Lambda / SQS / SNS is an advantage

• 100% remote possibility
• Extension of project possible

Ihr Kontakt

Ansprechpartner
Anna Salabai

Referenznummer
804120/1

Kontakt aufnehmen
E-Mail: anna.salabai@hays.ch

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