At a Glance
- Tasks: Design and optimise data solutions for finance reporting and transformation initiatives.
- Company: A growing insurer with a collaborative culture and strong career progression.
- Benefits: Competitive salary, hybrid work model, and excellent career development opportunities.
- Other info: Work closely with finance teams and contribute to impactful data projects.
- Why this job: Join a dynamic team and shape the future of finance reporting in a transformative role.
- Qualifications: Experience as a Data Engineer, strong SQL skills, and familiarity with Azure technologies.
The predicted salary is between 60000 - 90000 £ per year.
A growing insurer is looking for a Senior Data Engineer to join its expanding data function and play a key role in a major finance transformation programme. This is an opportunity to work closely with an experienced Head of Data and help shape the future of finance reporting and data capabilities within a highly collaborative organisation. The business offers the agility and visibility of a smaller insurer, with strong opportunities for progression and career development.
The Role
As a Senior Data Engineer, you will be responsible for designing, developing, and optimising data solutions that support finance reporting and transformation initiatives. You'll work closely with finance, reporting, and data teams to deliver high-quality, scalable data platforms and reporting capabilities. A key focus of the role will be supporting finance data requirements, including IFRS 17 reporting, while contributing to broader data engineering and transformation projects.
Key Responsibilities
- Design, build, and maintain robust data pipelines and data solutions.
- Support finance reporting and transformation initiatives across the business.
- Work closely with finance stakeholders to understand reporting and data requirements.
- Develop and optimise SQL-based data models and reporting datasets.
- Contribute to the ongoing development of cloud-based data platforms within Azure.
- Ensure data quality, governance, and best practice across the data estate.
- Collaborate with data engineers, developers, analysts, and business stakeholders.
Required Experience
- Proven experience as a Data Engineer, Senior Data Engineer, or similar role.
- Strong SQL development skills.
- Experience with Azure data technologies.
- Python experience would be highly advantageous.
- Previous experience working within the insurance sector.
- Strong understanding of supporting finance teams and finance-related data processes.
- Experience with IFRS 17 reporting is highly desirable.
- Exposure to finance transformation, finance reporting, or regulatory reporting projects.
Senior Data Engineer in City of London employer: JSS
Join a dynamic and growing insurer in London as a Senior Data Engineer, where you will be part of a collaborative team driving finance transformation initiatives. With a hybrid working model and a strong focus on employee development, this role offers not only competitive remuneration but also the chance to shape the future of finance reporting within a supportive environment. Experience the agility of a smaller organisation while enjoying significant opportunities for career progression and personal growth.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in City of London
✨Get Involved in Data Science Meetups
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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 at JSS.
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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.
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We think you need these skills to ace Senior Data Engineer in City of London
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.
