Data Engineer (80-100%)

About the role & team  

We are the largest data science and engineering team of Swiss Re and are looking to create a team of engineers dedicated to our insurance unit, that are enthusiastic about applying data engineering to real-world problems. Our focus is not only on machine learning and statistical modelling, but we also enjoy data engineering and bringing our models into production at scale.  

If you join us, you will be able to participate in a variety of interesting initiatives. For example, you will:  

• Generate insights from claims to smartly pay-out claims faster   

• Ensure we do not provide agro insurance cover in protected areas such as Amazon Rainforest  

• Craft data pipelines to collect data from internal and external sources, enrich it and develop complex data products  

  

We are a highly skilled and diverse team in Bratislava that solves diverse analytics projects around the globe. Our passion to learn is what connects us. We love to learn new skills and will support you to do the same! We reserve time for studying and organize our own upskilling sessions as well. In addition to projects for our clients, we also work on innovation projects which allow us to learn new methodologies and gain fresh experience.  

Joining us, you will learn the technologies that are used in modern data solutions with a focus on cloud technologies and distributed systems, but also gain experience in the application of big data methods to solve complex problems on real data, in a collaborative environment with colleagues from Swiss Re's international offices.  

  

About You  

Nobody is perfect and meets 100% of requirements. If you, however, meet some of the criteria below and are genuinely curious about the world of big data engineering, we will be happy to meet you.  

To be successful in the role, you need to have these technical skills and ambitions:  

• Degree in Computer Science or related field. We welcome different levels, including graduates.  

• Knowledge of Python.  

• Ambition to build production-grade data ingestion and transformation pipelines.  

 

Having the following experience and interests is a huge plus:  

• Experience in distributed computing/databases (e.g., Spark).  

• Interest in working close to data scientists and domain experts.  

• Interest in applying proper software engineering techniques during development.  

  

If you do not have some or any of those but are eager to learn them, get in contact with us.  

Thank you for taking the time to read our job advertisement. We look forward to getting to know you!  

 

The minimum gross monthly base salary for this role is 2200 EUR full time. Our final offer to you will be set up fairly, considering the skills and experience that you bring to the Swiss Re Group.

 

This job offer is suitable for people who have been impacted by the invasion of Ukraine.

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

 

 

 

About Swiss Re

 

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 14,000 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.

 

 

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