At a Glance
- Tasks: Design and maintain data pipelines for Treasury applications using large-scale datasets.
- Company: Join a leading financial institution focused on innovation and data-driven solutions.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on data quality and compliance.
- Why this job: Make an impact in finance by optimising data processes and supporting analytics.
- Qualifications: 6+ years in Data Engineering with strong skills in Python and Apache Spark.
The predicted salary is between 60000 - 80000 € per year.
We are looking for a Data Engineer to design, develop, and maintain robust data pipelines for Deposits and Treasury applications, working with large-scale datasets and enabling financial reporting and analytics use cases.
Responsibilities
- Design, develop, and maintain robust data pipelines for Deposits and Treasury applications.
- Work with large-scale structured and unstructured datasets using Apache Spark / PySpark.
- Develop high-quality, reusable, and efficient code in Python.
- Collaborate with business stakeholders to understand data requirements related to treasury products, liquidity, and deposits.
- Build and optimize ETL/ELT processes for data ingestion, transformation, and integration.
- Support data modelling for financial reporting and analytics use cases.
- Create and maintain data visualizations and dashboards using tools such as Amazon Quicksight, Power BI, Tableau, etc.
- Ensure data quality, governance, and compliance with financial regulations.
- Troubleshoot performance issues and optimize data workflows.
- Work closely with cross-functional teams including analysts, architects, and product owners.
Skills
Must have
- At least 6 years of experience in Data Engineering space.
- Strong experience building and maintaining data pipelines for banking data domains.
- Hands‑on expertise with Apache Spark / PySpark for large-scale data processing.
- Strong Python development skills with emphasis on reusable, efficient code.
- Solid ETL/ELT engineering experience (ingestion, transformation, integration).
- Experience supporting data modelling for reporting/analytics use cases.
- Exposure to BI/dashboarding tools such as Amazon Quicksight, Power BI, Tableau (or similar).
- Practical experience with data quality, governance, and working in regulated environments.
Nice to have
N/A
[DXCSynergy] Data Engineer - Treasury in London employer: Luxoft
Join our dynamic team as a Data Engineer in the heart of the financial sector, where innovation meets opportunity. We pride ourselves on fostering a collaborative work culture that encourages professional growth and development, offering access to cutting-edge technologies and projects that make a real impact in the banking domain. With a commitment to data quality and compliance, you'll thrive in an environment that values your expertise while providing unique advantages such as flexible working arrangements and a focus on work-life balance.
StudySmarter Expert Advice🤫
We think this is how you could land [DXCSynergy] Data Engineer - Treasury in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines, ETL processes, and any cool projects you've worked on. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills. Be ready to discuss your experience with Apache Spark, Python, and data modelling. Practise explaining complex concepts in simple terms – it shows you really understand your stuff!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications come directly from candidates who are excited about joining us. Plus, it makes it easier for us to keep track of your application and get back to you quickly.
We think you need these skills to ace [DXCSynergy] Data Engineer - Treasury in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Engineer role. Highlight your experience with data pipelines, Apache Spark, and Python. We want to see how your skills match what we're looking for!
Showcase Your Projects:Include specific projects where you've built or maintained data pipelines, especially in banking or finance. We love seeing real examples of your work that demonstrate your expertise!
Be Clear and Concise:When writing your application, keep it clear and to the point. Use bullet points for your achievements and responsibilities. We appreciate straightforward communication that gets right to the heart of your experience.
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. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Luxoft
✨Know Your Data Pipelines
Make sure you can talk confidently about your experience with building and maintaining data pipelines, especially in the banking domain. Brush up on your knowledge of ETL/ELT processes and be ready to discuss specific projects where you've optimised data workflows.
✨Showcase Your Coding Skills
Prepare to demonstrate your Python skills during the interview. Have examples ready that highlight your ability to write reusable and efficient code, particularly using Apache Spark or PySpark. You might even want to practice coding challenges to keep your skills sharp!
✨Understand the Business Context
Familiarise yourself with the treasury products and liquidity concepts relevant to the role. Be prepared to discuss how your data engineering work supports financial reporting and analytics, and how you can collaborate effectively with business stakeholders.
✨Visualisation Matters
Since you'll be working with BI tools like Amazon Quicksight, Power BI, or Tableau, make sure you can talk about your experience creating dashboards and visualisations. Bring examples of your work to the interview to illustrate your ability to present data insights clearly and effectively.
