Senior Data Engineer

About Team

The role is part of the newly formed Cashflow Enhancement team within the Subledger Input Preparation Product Area at Swiss Re's Finance IT division. The Product Owner is based in Switzerland, leading a global team responsible for developing the next generation of finance business applications.

The team uses a Lakehouse architecture with Azure Databricks, Azure Data Factory, Azure Data Lake (Delta Lake), and develops primarily in Python and PySpark for scalable data engineering.

Responsibilities

• Understand business requirements and convert them into technical specifications.
• Design and implement end-to-end data pipelines by combining input from various data sources.
• Collaborate with product owners and engineering leads to develop and maintain target architectures and align design decisions across the product area.
• Take ownership of functional and non-functional requirements, ensuring high levels of automation and performance.
• Perform peer code reviews, contribute to team discussions, and align solutions with architectural and quality standards.
• Meet with stakeholders to gather requirements and recommend efficient, scalable solutions.
• Participate in Agile Scrum and DevOps practices.
• Contribute to quarterly financial closing cycles and operations.
• Communicate effectively with customers and coordinate follow-up actions.

Requirement

• 5+ years of experience in designing and implementing end-to-end data pipelines and data models.
• Proficient in Python, PySpark, and SQL.
• Experience with Spark-based data lakes and Azure ecosystem (Azure Databricks, Azure Data Factory, Azure Data Lake).
• Expertise in relational databases such as Oracle or PostgreSQL.
• Experience with API integrations (REST/SOAP).
• Strong understanding of data engineering techniques and best practices.
• Clear communication skills with the ability to explain technical topics to non-technical audiences.
• Strong problem-solving skills and commitment to quality and timely delivery.
• Ability to operate in a DevOps environment and contribute to operational support.
• A strong desire to learn and adapt to emerging technologies.

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, or a related quantitative field.