Cloud Data Engineer

Vor 4 Tagen

Zürich, Zürich, Schweiz II-VI UK, Ltd. Vollzeit

We are looking for a highly skilled Cloud Data Engineer to join our team and help us design and implement a scalable data infrastructure for our hybrid on-premises and cloud environment.

The ideal candidate will have experience with cloud platforms (AWS or Azure), big data frameworks like Spark, and a proven track record of managing complex data pipelines.

Key Responsibilities:

  • Design and implement a cloud-based data infrastructure to support data integration across on-premises and cloud environments.
  • Implement and manage ETL processes, ensuring data accuracy and consistency through automated workflows within a hybrid infrastructure.
  • Collaborate with cross-functional teams to design and optimize data architecture for both on-premises and cloud storage solutions.
  • Manage data within a cloud environment (AWS or Azure) and utilize Databricks for data processing and analytics tasks.
  • Monitor, troubleshoot, and optimize data pipelines to ensure high performance, reliability, and scalability in a hybrid setup.

Required Skills and Qualifications:

  • Experience: Minimum 1+ years in data engineering, with hands-on experience in production environments, ideally in a hybrid data infrastructure.
  • Technical Skills:
    • Proficiency in Python and SQL for data manipulation and automation.
    • Experience with relational databases (e.g., Microsoft SQL Server).
    • Strong understanding of data modeling, including schema design and normalization.
    • Hands-on experience with cloud platforms (AWS or Azure) for data storage, processing, and analytics, alongside on-premises data systems.
    • Proficiency with ETL tools and pipeline orchestration (e.g., Apache Airflow, AWS Glue, Azure Data Factory).
    • Experience with big data frameworks like Spark for large-scale data processing.
    • Knowledge of version control systems, particularly Git, for collaboration and code management.
    • Understanding of data governance and quality standards.
  • Data Processing:
    • Experience using Databricks or similar platforms for scalable data processing and analytics.
  • Soft Skills:
    • Strong problem-solving skills with a detail-oriented approach.
    • Excellent communication skills for effectively conveying technical details to both technical and non-technical stakeholders.
    • Collaborative mindset with the ability to work effectively within a team environment.

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