At a Glance
- Tasks: Design and optimise data solutions for actuarial modelling in finance and life insurance.
- Company: Join M&G, a leading international savings and investments business with a rich history.
- Benefits: Flexible working, inclusive culture, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on diversity and inclusion.
- Why this job: Make a real impact by shaping data solutions that drive financial outcomes.
- Qualifications: Strong data engineering skills and experience in financial services or regulated environments.
The predicted salary is between 60000 - 80000 £ per year.
At M&G our purpose is to give everyone real confidence to put their money to work. As an international savings and investments business with roots stretching back more than 170 years, we offer a range of financial products and services through Asset Management, Life and Wealth. All three operating segments work together to deliver attractive financial outcomes for our clients, and superior shareholder returns.
The Data Engineer is responsible for designing, building, and optimising data solutions that enable reliable and efficient access to data for use in actuarial modelling and assumption setting. The Data Engineer will provide specialist expertise in data engineering, ensuring scalable, high-quality data pipelines and architectures are in place to support the use of policyholder data for actuarial modelling and assumption setting. The role contributes to shaping engineering standards and best practices, ensuring data is accessible, governed and aligned with business priorities.
Key accountabilities, skills & experience
- Design, build and maintain scalable data pipelines and data architectures to validate and transform data to meet actuarial modelling needs.
- Ensure data quality, integrity, and consistency through robust validation, monitoring, and governance practices.
- Collaborate with stakeholders to understand data requirements and translate them into efficient and effective technical solutions.
- Optimise data systems and processes to improve performance, reliability, and scalability.
- Provide technical expertise and guidance on data engineering approaches, tools, and best practices.
- Support integration of multiple data sources to create cohesive, accessible, and trusted datasets.
- Contribute to the continuous improvement of data platforms, frameworks, and engineering standards.
- Lead the work of other data engineers and analysts to ensure consistency and high standards across the team, including people management as required.
The skills you'll need:
- Strong expertise in data engineering concepts, including data pipelines, storage and transformation.
- Proficiency in data engineering tools, programming languages, and database technologies.
- Experience in performance tuning and optimisation.
- Programming and scripting for data processing (Spark, Spark SQL, Python, pyspark).
- Data modelling and architecture (in Azure Databricks).
- Understanding of data governance, security, and data quality management principles.
- Ability to design scalable and efficient data solutions aligned to business needs.
- Ability to communicate technical concepts clearly to both technical and non-technical audiences.
- Experience working in Financial Services or a similar heavily regulated environment.
- Experience in Life Insurance (desirable).
We have a diverse workforce and an inclusive culture at M&G plc, underpinned by our policies and our employee-led networks who provide networking opportunities, advice and support for the diverse communities our colleagues represent. Regardless of gender, ethnicity, age, sexual orientation, nationality, disability or long term condition, we are looking to attract, promote and retain exceptional people. We also welcome those who take part in military service and those returning from career breaks.
Senior Data Engineer (Finance/Life Insurance) in London employer: AMS CWS
At AMS, we pride ourselves on being an exceptional employer that champions inclusivity and diversity in the workplace. Our partnership with PwC allows us to offer meaningful roles like the SAP Analytics Cloud (SAC) Planning Lead, where you can thrive in a high-performance culture that values ethical standards and professional growth. With flexible remote working options and a commitment to employee development, we empower our team members to make a significant impact while enjoying a supportive and dynamic work environment in London.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Finance/Life Insurance) in London
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like AMS CWS before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
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We think you need these skills to ace Senior Data Engineer (Finance/Life Insurance) in London
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at AMS CWS, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to AMS CWS, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab AMS CWS’s attention and show the tangible impact of your work.
How to prepare for a job interview at AMS CWS
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at AMS CWS.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at AMS CWS.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at AMS CWS.
