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- 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.
- Why this job: Make an impact by modernising data platforms and optimising processes in finance.
- Qualifications: Expertise in Big Data, Hadoop, and real-time data processing required.
- Other info: Opportunity to work on strategic initiatives within a leading commodities group.
The predicted salary is between 36000 - 60000 £ per year.
Working for a renowned financial services organisation.
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 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.
- Experience replacing legacy ETL tools (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.
Senior Data Engineer (Big Data/ Hadoop/ Spark) (Financial Services) in London employer: hays-gcj-v4-pd-online
Contact Detail:
hays-gcj-v4-pd-online Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (Big Data/ Hadoop/ Spark) (Financial Services) in 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 refer you directly.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your previous projects, especially those involving Hadoop, Spark, and data pipelines. This will give potential employers a clear picture of what you can bring to the table.
✨Tip Number 3
Ace the interview! Research common interview questions for data engineering roles and practice your responses. Be ready to discuss your hands-on experience with multi-node Hadoop clusters and real-time data processing solutions.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Tailor your application to highlight your Big Data expertise and experience in financial services, and let’s get you that dream job!
We think you need these skills to ace Senior Data Engineer (Big Data/ Hadoop/ Spark) (Financial Services) in 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 our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how your background makes you a perfect fit for our team. Don’t forget to mention your hands-on experience with Hadoop and Spark!
Showcase Your Projects: If you've worked on any significant data platforms or pipelines, make sure to showcase them in your application. We love seeing real-world examples of your work, especially if they involve modernising ETL processes or optimising performance.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at hays-gcj-v4-pd-online
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Hadoop, Spark, and Apache Airflow. Brush up on your experience with multi-node Hadoop clusters and be ready to discuss how you've optimised performance in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data engineering, especially in financial services. Think about times when you improved job efficiency or replaced legacy ETL tools with modern solutions, and be ready to explain your thought process.
✨Understand the Business Context
Familiarise yourself with the financial services sector and the specific metals initiative mentioned in the job description. Being able to connect your technical skills to business outcomes will show that you understand the bigger picture and can contribute strategically.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy and the role's impact on their goals. This not only shows your interest but also gives you a chance to assess if the company aligns with your career aspirations and values.
