At a Glance
- Tasks: Lead the development of finance data solutions in a dynamic cloud environment.
- Company: Join a leading insurance organisation at a critical delivery stage.
- Benefits: Competitive day rate, flexible for strong candidates, and hybrid working.
- Other info: Ideal for hands-on professionals seeking to contribute to impactful programmes.
- Why this job: Make a real impact on high-stakes finance and actuarial projects.
- Qualifications: Strong Data Engineering experience in insurance and proficiency in Python/PySpark.
We are working with a leading insurance organisation seeking a Finance Data Engineering Lead to join a major programme at a critical stage of delivery. This is a hands-on role focused on building and delivering data solutions within an established cloud data environment.
The Role
You will play a key role in developing and deploying finance and actuarial data pipelines, supporting reporting, analytics and reconciliation capabilities.
Key responsibilities include:
- Developing Python / PySpark data pipelines within cloud platforms
- Building datasets and models for finance, actuarial and risk reporting
- Integrating with existing data ingestion and orchestration frameworks
- Supporting reconciliation, validation and data quality processes
- Collaborating with design and architecture teams to deliver aligned solutions
Experience Required
- Strong experience as a Data Engineer within insurance (essential)
- Proficiency in Python, PySpark and Spark-based processing
- Experience working with Databricks or similar cloud data platforms
- Exposure to finance, actuarial or regulatory reporting data
- Ability to operate within live programme environments and deliver at pace
Engagement Details
- Contract: Outside IR35
- Day Rate: £750 - £950 (flexible for strong profiles)
- Duration: 6-12 months
- Location: London (3 days per week onsite)
This role is ideal for someone who enjoys hands-on delivery, working within established environments, and contributing to high-impact programmes.
Finance Data Engineering Lead in London employer: Experis
Join a leading insurance organisation that values innovation and collaboration, offering a dynamic work culture where your contributions directly impact critical projects. With a focus on employee growth, you will have access to continuous learning opportunities and the chance to work with cutting-edge technologies in a hybrid environment in London. Enjoy competitive compensation and the flexibility of working three days a week onsite, making this an excellent opportunity for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Engineering Lead in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and data engineering space. Attend industry meetups or webinars, and don’t be shy about sharing your expertise. You never know who might have a lead on that perfect role!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python and PySpark projects, especially those related to finance and actuarial data. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss your experience with cloud platforms like Databricks and how you've tackled challenges in previous roles.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Finance Data Engineering Lead in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Finance Data Engineering Lead role. Highlight your experience with Python, PySpark, and any relevant cloud platforms like Databricks. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role. Share specific examples of your past work in insurance data engineering and how you’ve contributed to similar projects.
Showcase Your Hands-On Experience:Since this role is all about hands-on delivery, make sure to showcase your practical experience. Talk about the data pipelines you've built and how you've supported reporting and analytics in previous roles. We love seeing real-world applications!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for both of us!
How to prepare for a job interview at Experis
✨Know Your Tech Inside Out
Make sure you brush up on your Python and PySpark skills before the interview. Be ready to discuss specific projects where you've built data pipelines or worked with cloud platforms like Databricks. The more you can demonstrate your technical prowess, the better!
✨Understand the Insurance Landscape
Since this role is within the insurance sector, it’s crucial to have a solid grasp of finance and actuarial concepts. Familiarise yourself with regulatory reporting and how data plays a role in that. Showing that you understand the industry will set you apart from other candidates.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data quality and reconciliation processes. Think of examples from your past experience where you successfully tackled similar challenges. This will showcase your problem-solving skills and hands-on experience.
✨Show Your Collaborative Spirit
This role involves working closely with design and architecture teams, so be prepared to discuss how you’ve collaborated in previous roles. Highlight any experiences where teamwork led to successful project outcomes, as this will demonstrate your ability to fit into their culture.
