Senior Data Engineer – Data Analytics Platform in Zürich

• Design, build and maintain scalable data pipelines and backend services




• Support real-time decisioning, analytics, reporting and data collection




• Translate business/data requirements into appropriate data models and technical solutions




• Manage data transformation, integration and processing




• Develop high-quality, secure and well-tested code




• Build solutions that improve data governance, security and quality




• Implement processes and controls around Data Security and Data Quality




• Collaborate with developers and stakeholders while providing technical guidance

Job Description

• Design, build and maintain scalable data pipelines and backend services




• Support real-time decisioning, analytics, reporting and data collection




• Translate business/data requirements into appropriate data models and technical solutions




• Manage data transformation, integration and processing




• Develop high-quality, secure and well-tested code




• Build solutions that improve data governance, security and quality




• Implement processes and controls around Data Security and Data Quality




• Collaborate with developers and stakeholders while providing technical guidance

Requirements

• 5+ years’ Data Engineering experience, particularly ETL/ELT, Data Warehousing and BI




• 5+ years building end-to-end data systems/pipelines using Python and/or Scala




• Strong SQL skills, including data analysis, troubleshooting and root-cause analysis




• Hands-on experience with Databricks, PySpark, Spark Streaming and Delta Lake




• Experience with large-scale datasets and complex data transformations




• Strong experience with cloud-based data platforms, ideally Microsoft Azure




• Experience with Azure Data Lake / Blob Storage or comparable cloud storage




• Good understanding of data modelling and data architecture principles




• Experience working within CI/CD environments




• Exposure to event-driven architectures such as Kafka, Event Hubs or Apache Flink




• Experience with Docker / Kubernetes / Helm and containerised environments




• Knowledge of dbt and BI/reporting tools




• Strong communication skills with the ability to provide technical guidance/leadership

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