Data Engineer / team Group Sustainability/

Náplň práce, právomoci a zodpovednosti:
About the Role
Are you passionate about data and sustainability? Join our Product Area "Research & Sustainability" as a Data Engineer and play a key role in supporting our Group Sustainability initiatives. You will collaborate with experienced professionals and partners across the organization to help deliver impactful sustainability-related projects. This is an excellent opportunity to gain hands-on experience in data engineering while contributing to meaningful projects that drive positive change.

Key Responsibilities:
• Support the maintenance of data pipelines and products and help to design and build new ones in collaboration with our Lead Engineer.
• Contribute to writing high-quality, maintainable, and efficient code.
• Analyse datasets, identify patterns, and help create data-driven insights.
• Work with cross-functional teams to support the success of our products and ensure smooth collaboration.

About the Team
Our team drives data-driven insights and technological innovation within the Swiss Re Institute. We create tech solutions tailored for sustainability, working in a global environment with colleagues based in Zurich, Bratislava, Bangalore, and beyond. This is an exciting opportunity to learn from experienced professionals and grow in a dynamic, international setting.

Zamestnanecké výhody, benefity:
You can look forward to extra rewards and benefits including:
- Attractive performance-based bonus
- Ultra flexible working time in hybrid setup, allowing you to work also from home
- Modern office spaces in attractive location
- 5 additional days of holiday
- Lunch allowance fully paid by Swiss Re
- Referral bonus
- Pension & risk insurance contribution
- Sick days and sick leave support
- Public transport benefit
- Multisport card

Informácie o výberovom konaní:
We provide feedback to all candidates via email. If you have not heard back from us, please check your spam folder.

Požiadavky na zamestnanca:
Required Skills and Experience:
• Understanding of Data Engineering principles including CI/CD practices and demonstrated experience in either Data Modelling, ETL processes, big data technologies or data warehousing
• Experience with PySpark, Python/Scala, strong problem-solving abilities, experience in data analytics and a willingness to learn and grow is key

Nice to Have (not must):
• Worked in agile project environments and leveraging tools like Azure DevOps
• Experience in generating and interpreting data
• Knowledge in QA and testing frameworks
• Understanding of Typescript