Big Data Engineer

PROSTAFF Schweiz GmbH; Zürich; Vor Ort; CHF 120.000 - 150.000; Vollzeit

Zusammenfassung

PROSTAFF Schweiz GmbH seeks a Senior Data Engineer to design scalable data architectures and build distributed pipelines across cloud and on‑prem environments. You’ll enable data for operations, analytics, and ML workloads with reliable processing.

You’ll collaborate with data scientists, optimize pipelines for performance and cost, and work with Python/SQL, big data tech, and cloud services. Fluent German and English are required.

Qualifikationen

• Degree in computer science, mathematics or a related field.
• Several years of experience in technical roles, with strong Python and SQL skills.
• Sound knowledge of big data infrastructure, scalable databases and distributed processing.
• Good understanding of public cloud services such as AWS, Azure or Google Cloud.

Aufgaben

• Design and maintain scalable data architectures and pipelines across cloud and on-premises environments.
• Integrate diverse data sources and ensure processing is reliable and reproducible.
• Test and monitor distributed pipelines and estimate performance and costs for different use cases.
• Collaborate with data scientists to prepare datasets for machine learning and build dashboards that make processed data accessible to users.

Kenntnisse

Python

SQL

Big data

Distributed processing

DevOps practices

Ausbildung

Bachelor's degree in CS/Math related field

Tools

Spark

Hadoop

Hive

Airflow

Kubernetes

Jobbeschreibung

For one of our clients, we are looking for a Senior Data Engineer to design data architectures and build distributed pipelines across cloud and on-premises environments. Your work will make data ready for operational use, analytics and machine learning.

• Design and maintain scalable data architectures and pipelines across cloud and on-premises environments.

• Integrate diverse data sources and ensure processing is reliable and reproducible.

• Test and monitor distributed pipelines and estimate performance and costs for different use cases.

• Collaborate with data scientists to prepare datasets for machine learning and build dashboards that make processed data accessible to users.

• Degree in computer science, mathematics or a related field.

• Several years of experience in technical roles, with strong Python and SQL skills and a focus on maintainable software.

• Sound knowledge of big data infrastructure, scalable databases and distributed processing.

• Good understanding of public cloud services such as AWS, Azure or Google Cloud.

• Experience with or interest in tools such as Spark, Hadoop, Hive, Airflow or Kubernetes, and familiarity with relational or NoSQL databases and DevOps practices.

• Fluent German and English.