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- Tasks: Design and develop scalable data pipelines for a leading FinTech company.
- Company: Join a global FinTech business revolutionising data engineering.
- Benefits: Competitive salary, potential for contract extension, and career growth opportunities.
- Why this job: Be part of a collaborative team delivering AI-enabled data solutions that make an impact.
- Qualifications: Strong SQL skills and experience with Apache Spark and Python required.
- Other info: Dynamic environment with exposure to cutting-edge cloud technologies.
The predicted salary is between 36000 - 60000 £ per year.
G MASS is partnering with a global FinTech business to support the build-out of a next-generation data engineering capability within a large-scale enterprise data environment. This role sits within a highly technical engineering team focused on delivering AI-enabled, cloud-native data products used across the business. You'll join a collaborative engineering function responsible for designing and delivering robust, scalable data solutions. The work spans data ingestion, transformation, analytics and enablement, supporting both internal stakeholders and client-facing products.
Key responsibilities
- Design, develop and maintain scalable data pipelines for ingestion, transformation and storage
- Write efficient SQL queries to support data extraction, manipulation and analysis
- Use Apache Spark and Python to process large datasets and automate workflows
- Partner with data scientists, engineers and business stakeholders to translate requirements into data solutions
- Implement data quality checks and validation to ensure accuracy and reliability
- Analyse complex datasets to identify trends, patterns and anomalies
- Produce and maintain clear documentation covering data processes and architecture
- Support stakeholders with data visualisation and interpretation of outputs
Requirements
- Strong experience in SQL for data manipulation and analysis
- Hands-on experience with Apache Spark (Java, SQL or PySpark) and Python
- Experience working with large, complex datasets in enterprise environments
- Exposure to cloud data platforms (AWS, Azure or GCP) and big data technologies
- Confident communicator, comfortable working across technical and non-technical teams
- Background or exposure to financial services or capital markets
Nice to have
- Experience using Java in data processing or integration contexts
- Knowledge of ETL processes and data warehousing concepts
- Experience with data visualisation tools (Power BI, Tableau, Qlik)
- Familiarity with data science notebooks (e.g. Jupyter, Zeppelin)
Initial 6-month contract, with strong possibility of extension and/or permanency.
Data Engineer (FinTech) 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)
✨Tip Number 1
Network like a pro! Reach out to folks in the FinTech space, especially those who work with data engineering. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Apache Spark, and Python. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for technical interviews by brushing up on your SQL queries and data pipeline designs. Practise explaining your thought process clearly; it’s all about showing how you tackle problems!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented data engineers, and applying directly can give you a leg up in the hiring process.
We think you need these skills to ace Data Engineer (FinTech)
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 role in FinTech and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Technical Skills: When filling out your application, be sure to mention any hands-on experience you have with cloud platforms like AWS or Azure. We love seeing candidates who can demonstrate their technical prowess in real-world scenarios.
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 the role. Plus, it’s super easy to do!
How to prepare for a job interview at G MASS Consulting
✨Know Your Tech Stack
Make sure you’re well-versed in SQL, Apache Spark, and Python. Brush up on your skills and be ready to discuss how you've used these technologies in past projects. Being able to share specific examples will show that you can hit the ground running.
✨Understand the FinTech Landscape
Familiarise yourself with the financial services sector and how data engineering plays a role in it. Knowing the trends and challenges in FinTech will help you connect your technical skills to the business needs during the interview.
✨Prepare for Scenario Questions
Expect questions that ask you to solve real-world problems or design data solutions on the spot. Practise explaining your thought process clearly and logically, as this will demonstrate your problem-solving abilities and technical expertise.
✨Showcase Your Collaboration Skills
Since this role involves working with various stakeholders, be prepared to discuss how you’ve successfully collaborated with both technical and non-technical teams. Highlight any experiences where you translated complex data requirements into actionable solutions.
