At a Glance
- Tasks: Design and maintain data pipelines on Google Cloud Platform for analytics.
- Company: Central London insurance broker with a fast-paced environment.
- Benefits: £700 per day, outside IR35, with potential for contract extension.
- Other info: Opportunity to work in financial services with excellent career prospects.
- Why this job: Join a dynamic team and make an immediate impact in data engineering.
- Qualifications: Strong GCP experience, SQL skills, and ability to start immediately.
Contract: Outside IR35. Rate: £700 per day. Duration: 4 weeks (strong potential for extension). Location: Central London (client‑based role). Start Date: Immediate.
Role Overview
We are working with a central London‑based insurance broker who requires an experienced GCP Data Engineer to support a critical short‑term engagement, with a strong likelihood of follow‑on work. This role suits a hands‑on engineer who can quickly embed into an existing data team, take ownership of delivery, and add immediate value within a fast‑paced commercial environment.
Key Responsibilities
- Design, build, and maintain data pipelines on Google Cloud Platform (GCP).
- Work with services such as BigQuery, Cloud Storage, Dataflow, Pub/Sub, and Cloud Functions.
- Support ingestion, transformation, and optimisation of data for analytics and reporting use cases.
- Collaborate closely with analytics, data science, and engineering stakeholders.
- Ensure data quality, performance, and security best practices are applied.
- Troubleshoot and resolve data platform issues efficiently.
Skills & Experience Required
- Strong commercial experience as a GCP Data Engineer.
- Hands‑on expertise with BigQuery and modern data pipeline architectures.
- Solid SQL skills and experience with Python (or similar) for data engineering tasks.
- Understanding of data modelling, ETL/ELT patterns, and cloud‑native best practices.
- Experience working in financial services or insurance environments is highly desirable.
- Ability to start immediately and deliver with minimal onboarding.
Engagement Details
- Outside IR35
- £700 per day
- Initial 4‑week contract, with strong potential for extension
- Based with a Central London insurance broker
- Immediate start required
Contract GCP Data Engineer - £700/pd Outside IR35 in London employer: Jefferson Frank
Join a dynamic insurance broker in the heart of Central London, where you will be part of a collaborative and fast-paced environment that values innovation and expertise. As a Contract GCP Data Engineer, you'll have the opportunity to work on critical projects with a strong potential for extension, while benefiting from a culture that promotes professional growth and immediate impact. With competitive rates and a focus on data excellence, this role offers a rewarding experience for those looking to make a significant contribution in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Contract GCP Data Engineer - £700/pd Outside IR35 in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work in financial services or insurance. A quick chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your GCP projects, especially those involving BigQuery and data pipelines. This will give potential employers a taste of what you can bring to their team.
✨Tip Number 3
Be ready for a quick start! Since this role requires immediate availability, make sure you’re prepared to hit the ground running. Brush up on your SQL and Python skills so you can impress during interviews.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly helps us get to know you better and match you with the right roles.
We think you need these skills to ace Contract GCP Data Engineer - £700/pd Outside IR35 in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with GCP and data engineering. We want to see how your skills match the job description, so don’t be shy about showcasing your hands-on expertise with BigQuery and data pipelines!
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. We love seeing enthusiasm and a clear understanding of the responsibilities, so let your personality come through while keeping it professional.
Showcase Relevant Projects:If you've worked on projects that involved data ingestion, transformation, or analytics, make sure to mention them! We’re keen to see examples of how you’ve added value in previous roles, especially in fast-paced environments like financial services.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Jefferson Frank
✨Know Your GCP Inside Out
Make sure you brush up on your Google Cloud Platform knowledge, especially around BigQuery, Dataflow, and Pub/Sub. Be ready to discuss how you've used these tools in past projects and be prepared to share specific examples of data pipelines you've designed or maintained.
✨Showcase Your SQL and Python Skills
Since solid SQL skills and Python experience are crucial for this role, practice some common data engineering tasks beforehand. You might be asked to solve a problem on the spot, so having a few coding examples ready can really help you stand out.
✨Understand the Business Context
Familiarise yourself with the insurance sector and how data engineering plays a role in it. Being able to speak about how your work can impact analytics and reporting in a financial services environment will show that you’re not just technically skilled but also understand the business needs.
✨Prepare for Collaboration Questions
This role requires close collaboration with various stakeholders, so be ready to discuss your experience working in teams. Think of examples where you’ve successfully collaborated with data scientists or engineers, and how you handled any challenges that arose during those projects.
