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For Companies At a Glance
- Tasks: Join a mission-critical team to build and maintain data systems using AWS and modern technologies.
- Company: A globally respected financial institution with a cutting-edge platform engineering function.
- Benefits: Competitive salary, hands-on experience, and the chance to work on innovative projects.
- Why this job: Make a real impact in data engineering while solving complex technical challenges.
- Qualifications: 5+ years in AWS data engineering, strong Python and SQL skills, and knowledge of AI concepts.
- Other info: Unique opportunity to work in a greenfield role within a dynamic capital markets environment.
The predicted salary is between 48000 - 72000 £ per year.
About the Role
Join a mission-critical team within our firm’s cutting-edge platform engineering function, supporting platform for front-office developers (quants and strategists) 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 trends like AI Engineering, 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 Banks’ front-office. This is a rare greenfield role that 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
- 5 + years, hands-on experience in AWS data engineering technologies, including Glue, PySpark, Athena, Iceberg, Databricks, Lake Formation, and other standard data engineering tools.
- Strong 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.
- Experience with data governance, data quality, and data security best practices.
- 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 warehoused 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 scientist to build and deploy machine learning models.
AWS Data Engineer - AVP Capital Markets employer: Caspian One
Contact Detail:
Caspian One Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AWS Data Engineer - AVP Capital Markets
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving AWS, Python, and data pipelines. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions related to data engineering and cloud technologies. We recommend practicing with friends or using mock interview platforms to build your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace AWS Data Engineer - AVP Capital Markets
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 projects you've worked on. We want to see how your skills align with 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. Be sure to mention any experience with AI Engineering or capital markets.
Showcase Your Technical Skills: Don’t hold back on showcasing your technical skills in your application. Mention specific tools like Glue, PySpark, and Databricks that you've worked with. We love seeing candidates who are up-to-date with modern technologies!
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 submit all your documents in one go. Plus, we love seeing applications come directly from our site!
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 Problem-Solving Skills
Prepare to discuss specific technical challenges you've faced in previous roles, especially in a front-office or capital markets environment. Be ready to explain how you approached these problems and the impact of your solutions.
✨Understand the Business Context
Familiarise yourself with the financial institution's operations and how data engineering supports their goals. This will help you articulate how your role as an AWS Data Engineer can contribute to their success.
✨Stay Current with Trends
Demonstrate your passion for emerging technologies, particularly in AI Engineering. Be prepared to discuss any relevant projects or experiences you have with Generative AI and how they could apply to the role.