Senior Databricks & Azure Data Platform Engineer

PROSTAFF Schweiz GmbH; Indiana; Hybrid; Confidential; Full time

Job summary

PROSTAFF Schweiz GmbH is seeking an experienced Senior Data Engineer to support the development of a modern data platform in the insurance and reinsurance sectors. The successful candidate will design, build, and maintain a scalable data platform based on Databricks on Azure, centralizing fragmented data sources and ensuring data quality.

The role emphasizes building and optimizing data pipelines, creating reliable data layers for various business use cases, and facilitating integration with SAP and other source systems. A strong background in data governance, quality, and CI/CD concepts is essential.

Qualifications

• Several years of experience as a Senior Data Engineer or in a comparable role.
• Strong experience in building and maintaining data pipelines with Databricks.
• Good experience with cloud-based data platforms, ideally on Azure.
• Experience with CI/CD concepts in a data engineering environment.

Responsibilities

• Build, maintain and optimize data pipelines in Databricks.
• Design and implement scalable Lakehouse and Medallion Architecture concepts.
• Integrate and process data from multiple source systems, primarily SAP.
• Support or build CI/CD pipelines for data engineering workflows.

Skills

Data pipeline development

Databricks

Lakehouse Architecture

Data governance

Cloud platforms (Azure)

Tools

Power BI

SAP

Job description

PROSTAFF Schweiz GmbH is seeking an experienced Senior Data Engineer to support the development of a modern data platform in the insurance and reinsurance sectors. The successful candidate will design, build, and maintain a scalable data platform based on Databricks on Azure, centralizing fragmented data sources and ensuring data quality.

The role emphasizes building and optimizing data pipelines, creating reliable data layers for various business use cases, and facilitating integration with SAP and other source systems. A strong background in data governance, quality, and CI/CD concepts is essential.