Data Engineer

About the Position

Are you passionate about turning raw data into powerful, trusted insights that drive real business decisions? Do you thrive at the intersection of engineering, analytics, and innovation? If you're ready to build the data backbone of a forward-thinking organisation, we want to hear from you!

About the Role

As a Data Engineer within the Infotech Data & Analytics team, you'll play a pivotal role in designing, building, and optimising the data pipelines and platforms that fuel decision-making across GDTO. This is a hands-on, high-impact role where your engineering expertise meets analytical curiosity, and where the data you craft becomes a strategic asset for the entire organisation. You'll collaborate with talented engineers, architects, analytics professionals, and product owners to deliver scalable, reliable, and intelligent data solutions that truly make a difference.

Responsibilities

• Design and develop robust, scalable data pipelines and transformation workflows that ensure high-quality, trusted data flows seamlessly across the organisation
• Build and maintain data models and transformation logic, ensuring data assets are well-structured, thoroughly documented, and ready for analytical consumption
• Engineer and optimise solutions on cloud platforms such as Palantir Foundry, leveraging data-oriented cloud services to maximise performance and reliability
• Write clean, efficient code using Python/PySpark to process, transform, and analyse large-scale datasets with precision and purpose
• Collaborate closely with product owners, data architects, analysts, and end users to translate complex business requirements into elegant technical data solutions
• Bring data to life through visualisation by designing and building compelling, intuitive dashboards and analytical applications using tools such as Palantir Workshop, ensuring that insights are accessible, actionable, and impactful for end users
• Troubleshoot and resolve complex data issues with clarity of thought and a structured problem-solving approach, keeping stakeholders informed of progress and outcomes
• Contribute to the evolution of the data and analytics platform, identifying opportunities to improve scalability, reusability, and data quality in alignment with product owner priorities
• Champion data best practices, including data governance, lineage, and documentation, to ensure data assets are trusted, transparent, and actionable
• Stay current with emerging technologies and trends in data engineering, cloud platforms, and AI to continuously enhance team capabilities and drive innovation

Requirements

• Data Engineering, Transformation & Cloud Platform Expertise: Proven hands-on experience designing and building data pipelines, transformation models, and analytical data assets at scale. You know how to move data and how to make it genuinely valuable. You bring strong hands-on experience with Palantir Foundry, Azure, or another major cloud platform, including solid knowledge of data-oriented cloud services and architecture patterns
• Python / PySpark Proficiency: Strong programming skills in Python and/or PySpark for data processing, transformation, and analysis across large, complex datasets
• Data Visualisation: A strong ability to translate complex data into compelling, intuitive visual stories, whether through interactive dashboards, analytical applications, or self-service reporting tools built on Palantir Workshop, Power BI, or similar platforms. You understand that great data engineering doesn't stop at the pipeline, it ends with insights that people can actually use and act on
• AI-Assisted Development & Pipeline Automation: Practical experience leveraging AI coding assistants (such as GitHub Copilot or similar tools) to accelerate and enhance development workflows, as well as hands-on exposure to AI-driven pipeline automation to build smarter, more efficient and self-optimising data solutions
• Analytical Mindset: A natural ability to see the bigger picture in data, understanding not just how to move data, but how to make it insightful and impactful for end users

Nice to Have

• Curiosity & Adaptability: A growth mindset and genuine enthusiasm for picking up new tools, platforms, and methodologies as the data landscape continues to evolve
• Agile & Product-Oriented Ways of Working: Familiarity with agile methodologies and experience working in product-oriented teams, contributing to sprint planning, backlog refinement, and iterative delivery

We Offer

• Base Salary: EUR 2,400 - EUR 4,100 per month (for a full-time role)
• Performance-Based Variable Compensation: An attractive component designed to recognise your achievements
• Global and Location-Specific Benefits: A variety of benefits tailored to your location and role

About the Company

Swiss Re is one of the world’s leading providers of reinsurance, insurance and other forms of insurance-based risk transfer, working to make the world more resilient. We anticipate and manage a wide variety of risks, from natural catastrophes and climate change to cybercrime. Combining experience with creative thinking and cutting-edge expertise, we create new opportunities and solutions for our clients. This is possible thanks to the collaboration of more than 15,000 employees across the world.

Our success depends on our ability to build an inclusive culture encouraging fresh perspectives and innovative thinking. We embrace a workplace where everyone has equal opportunities to thrive and develop professionally regardless of their age, gender, race, ethnicity, gender identity and/or expression, sexual orientation, physical or mental ability, skillset, thought or other characteristics. In our inclusive and flexible environment everyone can bring their authentic selves to work and their passion for sustainability.

If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience.

We may use AI-powered tools to support the review and evaluation of applications for this position. These tools provide additional insights to our recruitment teams, but all hiring decisions are carefully reviewed and made by people. To learn more about how we use AI in recruitment and how we handle your personal data, please review our Data Privacy Statement before applying.

Keywords

Data Engineer, Data Engineering, Transformation, Cloud Platform Expertise, Python, PySpark, Data Visualisation

Reference Code

139584