Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and deliver scalable data solutions for a cutting-edge FinTech business.
- Company: Dynamic consultancy firm in the heart of Greater London.
- Benefits: Competitive pay, potential for contract extension, and career growth opportunities.
- Why this job: Join a tech-savvy team and shape the future of finance with AI-powered data pipelines.
- Qualifications: Strong SQL skills, hands-on experience with Apache Spark and Python, cloud platform familiarity.
- Other info: Exciting 6-month contract with the chance to secure a permanent position.
The predicted salary is between 42000 - 84000 £ per year.
A consultancy firm is seeking a Data Engineer to join their technical team in Greater London. The role involves designing and delivering scalable data solutions across a FinTech business.
Candidates should have strong experience in SQL, hands-on skills with Apache Spark and Python, and familiarity with cloud platforms like AWS or Azure.
This is an initial 6-month contract with potential for extension or permanency.
Data Engineer, FinTech — AI-Powered Cloud Data Pipelines employer: G MASS Consulting
Contact Detail:
G MASS Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer, FinTech — AI-Powered Cloud Data Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech space, especially those who work with data. LinkedIn is your best mate here; drop them a message and see if they can share insights or even refer you to open positions.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with SQL, Apache Spark, and Python. This will not only demonstrate your expertise but also give you something tangible to discuss during interviews.
✨Tip Number 3
Prepare for technical interviews by brushing up on common data engineering challenges. Practice coding problems related to data pipelines and cloud platforms like AWS or Azure. We all know practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the easiest way to get your application noticed. Plus, we’re always on the lookout for talented individuals like you to join our team.
We think you need these skills to ace Data Engineer, FinTech — AI-Powered Cloud Data Pipelines
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, Apache Spark, and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the Data Engineer position and how your background in FinTech makes you a great fit for our team.
Showcase Your Cloud Knowledge: Since familiarity with AWS or Azure is key, mention any specific projects where you’ve used these platforms. We love seeing practical examples of how you’ve tackled challenges in the cloud!
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 in our technical team!
How to prepare for a job interview at G MASS Consulting
✨Know Your Tech Inside Out
Make sure you brush up on your SQL, Apache Spark, and Python skills. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Familiarise Yourself with Cloud Platforms
Since the role involves cloud solutions, it’s crucial to have a solid understanding of AWS or Azure. Prepare to talk about your experience with these platforms and how you've leveraged them in past projects.
✨Showcase Your Problem-Solving Skills
Data engineering often involves troubleshooting and optimising data pipelines. Think of examples where you identified issues and implemented effective solutions, and be ready to share these during the interview.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the consultancy's approach to data engineering, their tech stack, and how they envision the role evolving. This shows your genuine interest and helps you assess if it's the right fit for you.
