Associate Business Analyst
Confirmed on the employer's own hiring board on Oct 19, 2026. First seen by Alion on Sep 30, 2026.
About the role
In this role, your key business responsibilities will include:
- Translate business requirements into effective data mapping/ingestion solutions
- Develop sophisticated data transformation processes using ETL, Python, SQL, and other tools to deliver high-quality data for Life & Health stakeholders
- Design and execute test cases to validate data transformations, resolving discrepancies to ensure data integrity
- Perform rigorous data quality checks to ensure reliable data ingestion and consumption
- Analyze large, complex datasets to identify trends and support strategic business decisions
- Recommend and implement solutions for business challenges, including process improvements, system enhancements, or user training
- Serve as a liaison between business stakeholders and data experts, leading data-driven projects
- Conduct ad hoc analyses to address specific business questions or support new initiatives
- Collaborate with peers to apply advanced analytics and automate smart business decisions
About the team
The Client Data Management [CDM] team is part of Business Excellence delivering on the promise of a stable end-to-end operating platform for Life & Health Reinsurance [L&H Re]. Their mission is to make client data accessible to stakeholders by systematically acquiring and ingesting it. The team utilizes advanced analytics techniques to generate valuable insights for L&H Re. With a continuous improvement mindset, they strive to enhance data, systems, and processes for both their own use and their stakeholders.
About you
- Bachelor's degree in computer science with 3 to 5 years of relevant experience
- Excellent communication skills with the ability to present complex data and insights clearly to stakeholders
- Strong skills in data mapping, ETL processing, and data integration
- Proficiency in SQL and Python, with experience working with relational databases
- Experience working with large volumes of structured and unstructured data
- Familiarity with best practices of data management and governance
- Proven strategic, analytical, and conceptual thinking abilities
- Effective communication skills, with the ability to present complex data and insights to stakeholders clearly and concisely
These are additional nice to have:
- Experience with large language models (LLMs) and AI-assisted analytics for insight generation
- Data visualization skills and experience with tools like Tableau or Power BI
- Knowledge of Life & Health Reinsurance
- Experience with agile methodologies and project management
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. We cover both Property & Casualty and Life & Health. 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:
Reference Code: 139473