Senior Data Engineer – Data Analytics Platform

Swisslinx; Zürich; Vor Ort; CHF 120.000 - 170.000; Vollzeit

Zusammenfassung

Swisslinx is seeking a Senior Data Engineer in Zürich to design, build and maintain scalable data pipelines and backend services. You will support real-time decisioning, analytics, reporting and data collection, translating business needs into robust data models and technical solutions.

The role requires 5+ years in data engineering with Python/Scala, strong SQL, and hands-on Databricks, PySpark, Delta Lake, and Azure experience.

Qualifikationen

• 5+ years’ Data Engineering experience, including ETL/ELT, Data Warehousing and BI.
• 5+ years building end-to-end data systems/pipelines using Python and/or Scala.
• Strong SQL skills for data analysis, troubleshooting and root-cause analysis.
• Hands-on Databricks, PySpark, Spark Streaming and Delta Lake experience.
• Experience with large datasets and complex transformations.
• Cloud data platforms, ideally Microsoft Azure; Azure Data Lake/Blob Storage.
• CI/CD experience; event-driven architectures (Kafka, etc.).
• Docker/Kubernetes/Helm in containerised environments; dbt knowledge.

Aufgaben

• 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.

Kenntnisse

ETL/ELT pipelines

Data Warehousing

BI analytics

SQL data analysis

Python

Scala

CI/CD

Leadership/guidance

Communication

Tools

Databricks

PySpark

Spark Streaming

Delta Lake

Azure Data Lake/Blob

Docker

Kubernetes

Helm

dbt

BI tools

Jobbeschreibung

• 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