Associate Data Engineer

Are you passionate about transforming complex financial data into actionable insights Join our innovative Reporting Solutions team where you'll leverage cutting-edge technologies to build the data backbone that powers Swiss Re's financial reporting ecosystem. This is your opportunity to make a significant impact in a collaborative global environment that values technical excellence and continuous innovation.

About the Role

As an Associate Data Engineer in our Reporting Solutions team, you'll be at the intersection of finance and technology, creating data solutions that enable informed decision-making across Swiss Re. You'll collaborate with stakeholders to understand business needs and develop robust data pipelines and reporting solutions that drive efficiency and innovation.

Key Responsibilities

• Collaborate closely with stakeholders to understand business questions and clearly specify key metrics and acceptance criteria for reporting solutions
• Build and maintain the core data backbone by integrating multiple Finance data systems using PySpark and tools within the Palantir Foundry environment
• Develop comprehensive data and reporting solutions that address business requirements for the wider Finance organization
• Implement testing strategies to ensure deliverables meet specifications, including system performance and report timeliness
• Ensure smooth operation of existing reporting platforms through structured change management activities
• Participate in ad-hoc projects and work collaboratively with team members to address evolving business needs
• Stay informed about the latest trends and best practices in data engineering and financial data analysis

About the Team

Global Finance Operations & Transformation (GFO&T) is responsible for the accounting and reporting of accurate and consistent financial information for Swiss Re. Our Reporting Solutions team is at the core of GFO&T, providing a flexible and stakeholder-centric reporting infrastructure for the entire department. We are a diverse team based out of Zürich, Bratislava, and Bangalore, committed to bringing alive the Finance of the Future. We transform our Finance operating model by standardizing, automating, and integrating our Reporting & Processes along the Value Chain. We foster innovation by driving Business Use Cases in the areas of User Experience and Data Management, working cross-functionally with colleagues in Finance, IT, and other departments to eliminate silos .

About You

You are a curious and collaborative professional who thrives in a dynamic environment. You have a passion for transforming complex data into meaningful insights and enjoy working at the intersection of technology and finance. Your strong technical skills are complemented by excellent communication abilities, allowing you to translate business needs into technical solutions effectively.

We are looking for candidates who meet these requirements

• 1-5 years of working experience in data engineering and reporting
• Proficiency in PySpark for data processing and management
• Experience with Palantir Foundry & its applications (building pipeline using code-repository, creating data-health Checks & Expectations, data analysis in Contour) is an advantage.
• Knowledge of Spark and optimizing spark-based pipelines
• Ability to convert business problems into technical implementations
• University degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Engineering, or Information Technology)
• Excellent command of spoken and written English with ability to present to senior management

These are additional nice to haves:

• Familiarity with Financial Reporting
• Knowledge of Visualization tools or TypeScript
• Experience in data model design and implementation
• Process and delivery mindset aspiring for methodological and operational improvements
• Experience working in a global, cross-functional team environment

Our company has a hybrid work model where the expectation is that you will be in the office at least three days per week