At a Glance
- Tasks: Build and maintain data systems, pipelines, and architectures for accurate and secure data processing.
- Company: Top investment bank with a cutting-edge platform engineering team.
- Benefits: Hybrid work model, competitive contract rates, and exposure to innovative technologies.
- Other info: Opportunity to work with advanced tools like Databricks and Snowflake.
- Why this job: Join a high-impact team and tackle real-world data challenges in finance.
- Qualifications: Experience in AWS data engineering and proficiency in Python and SQL.
The predicted salary is between 60000 - 80000 £ per year.
AWS Data Engineer – Top Investment Bank
Location: London
Hybrid: 2/3 days per week in London office
Contract: 6 - 12 Month Initial Contract (View to be extended)
Must Have: Financial Services / Front-Office Experience
About the Role
Join a mission-critical team within our firm’s cutting-edge platform engineering function, supporting the business in a unique hands-on opportunity within a focused, high-impact team. You’ll be at the forefront of data and cloud-native engineering, working with modern technologies across AWS, On-premise Kubernetes, Python, and data pipelines, while engaging directly with key internal platforms and front-office business developers. If you are passionate about solving hard technical problems, staying current with technology trends and want to make a difference in a globally respected financial institution, this role is for you.
The successful AWS Data Engineer candidate will have the chance to make a significant impact in designing the platform and working on cutting-edge technologies like Databricks and Snowflake in the heart of a leading global Investment Bank. This rare project offers the opportunity to solve the ultimate data pipeline challenge faced by all banks, working closely with various businesses and gaining an overview of many different sectors.
What We’re Looking For
- Hands-on experience in AWS data engineering technologies, including Glue, PySpark, Athena, Iceberg, Databricks, Lake Formation, and other standard data engineering tools.
- Experience engineering in a front-office/capital markets environment.
- Previous experience in implementing best practices for data engineering, including data governance, data quality, and data security.
- Proficiency in data processing and analysis using Python and SQL.
- Strong knowledge of market data and its applications.
- Understanding of Generative AI concepts, along with hands-on experience in developing and deploying AI applications in real-world environments.
Nice to Have
- Experience with other data engineering tools and technologies.
- Knowledge of Machine Learning / AI and data science concepts.
Accountabilities
- To build and maintain the systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
- Build and maintenance of data architectures pipelines that enable the transfer and processing of durable, complete and consistent data.
- Design and implementation of data warehouses and data lakes that manage the appropriate data volumes and velocity and adhere to the required security measures.
- Development of processing and analysis algorithms fit for the intended data complexity and volumes.
- Collaboration with data scientists to build and deploy machine learning models.
AWS Data Engineer - Investment Banking employer: Caspian One
As a leading global investment bank, we pride ourselves on fostering a dynamic and inclusive work culture that encourages innovation and professional growth. Our London office offers a unique opportunity to work at the forefront of data engineering within a mission-critical team, where you will engage with cutting-edge technologies and have a direct impact on high-stakes projects. With a commitment to employee development and a collaborative environment, we provide our team members with the tools and support they need to excel in their careers while making meaningful contributions to the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land AWS Data Engineer - Investment Banking
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at a top investment bank. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your hands-on experience with AWS tools like Glue and Databricks. Talk about projects you've worked on and how you tackled challenges – this is your time to shine!
✨Tailor Your Approach
Make sure you tailor your conversations to highlight your front-office experience and understanding of market data. Show them you know what it takes to thrive in a fast-paced investment banking environment.
✨Apply Through Our Website
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and take the initiative to reach out directly.
We think you need these skills to ace AWS Data Engineer - Investment Banking
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AWS Data Engineer role. Highlight your hands-on experience with AWS technologies and any relevant financial services background. We want to see how your skills match what we're looking for!
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 you can contribute to our mission-critical team. Keep it concise but impactful, and don’t forget to mention your experience in front-office environments.
Showcase Your Technical Skills:In your application, be sure to showcase your technical skills, especially with tools like Glue, PySpark, and Databricks. We love seeing specific examples of how you've used these technologies to solve problems or improve processes in your previous roles.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing candidates who take that extra step!
How to prepare for a job interview at Caspian One
✨Know Your Tech Inside Out
Make sure you’re well-versed in AWS data engineering technologies like Glue, PySpark, and Databricks. Brush up on your Python and SQL skills too, as you'll likely be asked to demonstrate your proficiency during the interview.
✨Showcase Your Financial Services Experience
Since this role is within investment banking, highlight any relevant experience you have in financial services or front-office environments. Be ready to discuss how your background can contribute to solving complex data challenges in this sector.
✨Prepare for Technical Problem-Solving
Expect to face technical questions that assess your problem-solving abilities. Practice explaining your thought process clearly and concisely, especially when discussing data governance, quality, and security best practices.
✨Engage with Generative AI Concepts
Familiarise yourself with Generative AI and its applications in data engineering. Be prepared to discuss any hands-on experience you have in developing AI applications, as this could set you apart from other candidates.
