Data Engineer (Snowflake / Finance Data Platform)
PROSTAFF Schweiz GmbH Zurich, Zurich, Switzerland
Staffing and Recruiting · 201-500 employees
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About the role
The Data Engineer will design, develop, and maintain scalable data pipelines to integrate financial data into Snowflake. They will also enhance existing Finance Data Marts and ensure data quality and reliability across all financial data flows.
What they look for
Requirements
Candidates must have several years of hands-on experience in Data Engineering and Data Warehousing with strong expertise in Snowflake and SQL. Proficiency in Python, data modeling, and modern ETL/ELT integration architectures is required.
Full description
For our client in the financial services industry, we are looking for an experienced Data Engineer specializing in Snowflake, SQL, and Python.
In this role, you will support the further development of a modern Finance Data Platform. The primary focus is on integrating financial data into Snowflake, enhancing existing Finance Data Marts, and building scalable, reliable data pipelines.
- Design, develop, and maintain data pipelines from various Finance applications and source systems into Snowflake
- Further develop existing Finance Data Marts and underlying data models
- Integrate new Finance data sources using modern ETL/ELT technologies and data integration patterns
- Ensure data quality, reliability, and availability across Finance data flows
- Analyze, troubleshoot, and resolve data integration issues, implementing sustainable solutions
- Support automation, deployment processes, and modern engineering practices, including CI/CD and DevOps
- Collaborate closely with Finance teams, application developers, architects, and other technical stakeholders
- Translate business requirements into scalable technical solutions
- Document data flows, data models, and implemented technical solutions
- Several years of hands-on experience in Data Engineering and Data Warehousing
- Strong expertise in Snowflake and SQL, particularly in designing and building scalable data pipelines
- Solid experience in data modelling, ideally including Data Vault
- Strong understanding of ETL/ELT processes and modern data integration architectures
- Practical experience with Python for data processing, integration, and automation
- Knowledge of CI/CD pipelines, DevOps practices, and deployment automation is an advantage
- Strong analytical, problem-solving, and communication skills
- Experience working with financial data, Accounting, or Controlling is an advantage
- Structured, independent, and solution-oriented working approach
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