Expert Analytics Engineer (80-100%)
Manchester, GB
RDS (Risk Data & Services) are building Platform as a Service for some of the world’s largest corporate entities to help them mitigate a wide variety of risks, through first-in-class analytics and varied data sources.
We’re looking for another engineer to join our global team, to continue helping our client base understand their data and risk against an ever-changing landscape of climate change and natural catastrophes.
About the role
We are building a greenfield, cloud-native risk data and services platform to deliver cutting-edge risk intelligence insights and risk transfer solutions to our clients.
This is an opportunity to join a fast-paced working environment that leverages the latest technologies to provide unique and compelling solutions in a competitive marketplace.
We operate with a startup mentality, challenge boundaries, and strive to combine leading-edge technology capabilities with new and emergent business models.
Your responsibilities:
- Engineer and maintain a host of pipelines from initial ingest to delivery on platform and within solutions
- Help design and develop a robust operational concept with health checks and good DevSecOps practices
- Ensure deployment and testing standards for solutions and platform are adhered to
- Investigate and effectively work with colleagues across domains and within the wider-engineering community to monitor and maintain data quality
- Work with Product Owners, Sales, UX Designers and Solutions Architects to understand and evaluate requirements from clients and internal users
- Work with an Agile mentality to deliver high value quickly in an iterative manner
About the team
Join a diverse and talented team of engineers (10+) based out of our Manchester hub, located centrally in the city. Benefit from flexible working arrangements where you own the way you work, and have a career supported by likeminded people.
About you
A detail-oriented, team-player with excellent communication skills, a continuous learning mindset and a willingness to share knowledge across domains.
-
Strong programming skills in writing clean, optimized, Python and PySpark
-
Experience with Microsoft Azure services, specifically the Microsoft Fabric suite of applications
-
Experience building reliable and robust datasets and interacting with external APIs
-
4+ years’ experience across software or analytics engineering
-
Infrequent travel required.
Nice to have
-
Experience with Palantir Foundry
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.
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.
Keywords:
Reference Code: 131985
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile APIs Azure Data quality Engineering Pipelines PySpark Python Testing UX
Perks/benefits: Flex hours Startup environment
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.