Senior Data Engineer – Finance Transformation (Azure, IFRS17)

Senior Data Engineer – Finance Transformation (Azure, IFRS17)

Full-Time 50000 - 65000 Β£ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design data solutions to enhance finance reporting and transformation in a hybrid role.
  • Company: Join JSS, a leading player in the insurance sector based in London.
  • Benefits: Enjoy a competitive salary and flexible working arrangements.
  • Other info: Collaborate closely with finance and data teams in a dynamic environment.
  • Why this job: Make a real impact on finance transformation with cutting-edge data solutions.
  • Qualifications: Proven experience in data engineering and strong knowledge of Azure required.

The predicted salary is between 50000 - 65000 Β£ per year.

JSS is looking for a Senior Data Engineer to join its insurance team in London. This hybrid role involves designing data solutions that enhance finance reporting and transformation. You'll collaborate closely with finance and data teams to develop scalable data platforms and ensure data quality.

The ideal candidate will have proven experience in data engineering, strong knowledge of Azure, and a background in the insurance sector.

Senior Data Engineer – Finance Transformation (Azure, IFRS17) employer: JSS

At JSS, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation. Our London-based team enjoys the benefits of hybrid working, competitive remuneration, and ample opportunities for professional growth in the rapidly evolving field of finance transformation. Join us to make a meaningful impact in the insurance sector while advancing your career in a supportive environment.

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Contact Details:

JSS Recruitment Team

StudySmarter Expert Advice🀫

We think this is how you could land Senior Data Engineer – Finance Transformation (Azure, IFRS17)

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like JSS!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer – Finance Transformation (Azure, IFRS17) at JSS.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like JSS.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Data Engineer – Finance Transformation (Azure, IFRS17) at JSS, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Engineer – Finance Transformation (Azure, IFRS17)

Data Engineering
Azure
Finance Reporting
Data Solutions Design
Data Quality Assurance
Collaboration Skills
Scalable Data Platforms

Some tips for your application 🫑

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at JSS, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at JSS. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at JSS

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at JSS!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.