At a Glance
- Tasks: Design and deliver scalable data solutions using Big Data technologies.
- Company: Join a renowned financial services organisation with a focus on innovation.
- Benefits: Enjoy flexible working options and a dynamic work environment.
- Other info: Opportunity to work on strategic initiatives and enhance your career.
- Why this job: Make a real impact by modernising data platforms and optimising processes.
- Qualifications: Expertise in Big Data, Hadoop, Spark, and experience in financial services.
The predicted salary is between 36000 - 60000 € per year.
Your new company
Working for a renowned financial services organisation.
Your new role
We're looking for a Senior Data Engineer to design and deliver scalable on-prem, high-quality data solutions for low/high-level data platforms that power analytical and business insights. This is a hands-on role suited to someone with strong data engineering and big data expertise, ideally gained within financial services. Joining a leading commodities, metals, trading, and exchange group, you will support a strategic metals initiative focused on reducing on-prem platform costs and modernising legacy ETL processes. You'll help design and build a new on-prem data platform aligned to the metals strategy while developing and maintaining scalable data pipelines and analytics infrastructure. Using Hadoop, Big Data, and Spark technologies, you will ensure data quality through automated validation, monitoring, and testing. You will also enable seamless integration across data warehouses and data lakes, contributing to a robust, scalable, and resilient enterprise data ecosystem.
What you'll need to succeed
- Vast Data Engineering expertise with Big Data technologies.
- Experience designing and building on-prem data platforms, from high-level architecture to detailed technical design.
- Hands-on experience configuring multi-node Hadoop clusters, including resource management, security, and performance tuning.
- Strong Big Data engineering background using Apache Airflow, Spark, dbt, Kafka, and Hadoop ecosystem tools.
- Knowledge of RDBMS systems (PostgreSQL, SQL Server) and familiarity with NoSQL/distributed databases such as MongoDB.
- Proven delivery of streaming pipelines and real-time data processing solutions.
- Improved job efficiency and reduced runtimes through Apache Spark optimisation and development.
- Some experience with containerisation (Docker, Kubernetes) and CI/CD pipelines.
- Delivered streaming pipelines and real-time data processing solutions.
- Experience replacing legacy ETL tools (e.g., Informatica) with modern data engineering pipelines and platform builds.
- Proven background working within financial services environments.
What you'll get in return
Flexible working options available.
What you need to do now
If you're interested in this role, click 'apply now' to forward an up-to-date copy of your CV, or call us now.
Senior Data Engineer (Big Data/ Hadoop/ Spark) in City of London employer: Hays
As a leading financial services organisation, we pride ourselves on fostering a dynamic work culture that values innovation and collaboration. Our commitment to employee growth is evident through flexible working options and opportunities to engage in cutting-edge projects within the metals trading sector. Join us to be part of a forward-thinking team where your expertise in Big Data technologies will directly contribute to modernising our data platforms and driving impactful business insights.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer (Big Data/ Hadoop/ Spark) in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the hunt for a Senior Data Engineer role. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Big Data technologies like Hadoop and Spark. This will give potential employers a taste of what you can do and set you apart from the competition.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with data pipelines and real-time processing. Practising common interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Senior Data Engineer (Big Data/ Hadoop/ Spark) in City of London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Big Data technologies and any relevant projects you've worked on, especially in financial services. We want to see how your skills align with what we're looking for!
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention your hands-on experience with Hadoop, Spark, and any other tools listed in the job description. We love seeing specific examples of how you've used these technologies to solve real-world problems.
Keep It Clear and Concise:When writing your application, keep it clear and concise. Use bullet points where possible to make it easy for us to read through your qualifications. We appreciate a well-structured application that gets straight to the point!
Apply Through Our Website:Finally, make sure to apply through our website! This helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do – just click 'apply now' and follow the prompts!
How to prepare for a job interview at Hays
✨Know Your Tech Inside Out
Make sure you’re well-versed in the Big Data technologies mentioned in the job description, like Hadoop and Spark. Brush up on your hands-on experience with multi-node Hadoop clusters and be ready to discuss specific projects where you’ve configured them.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've tackled challenges in data engineering, especially around optimising Apache Spark or replacing legacy ETL tools. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Understand the Financial Services Landscape
Since this role is within a financial services organisation, it’s crucial to demonstrate your understanding of the industry. Familiarise yourself with current trends and challenges in financial data management, and be ready to discuss how your skills can address these.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy and the specific metals initiative. This shows your genuine interest in the role and helps you assess if the company aligns with your career goals.
