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- Tasks: Build and maintain scalable Data Lakes and pipelines in a dynamic environment.
- Company: Leading SaaS platform in financial services with over 20 years of experience.
- Benefits: Competitive salary, bonus, and benefits with opportunities for career growth.
- Why this job: Join a cutting-edge team and shape the future of data in finance.
- Qualifications: Experience in Python, AWS, and data engineering; eagerness to learn new tech.
- Other info: Exciting opportunity to lead in a growing Data Engineering division.
The predicted salary is between 75000 - 85000 £ per year.
Location: London - 2x per month
Salary range: £75,000-£85,000 + 10% bonus + benefits
Purpose: Build and maintain large, scalable Data Lakes, processes and pipelines
Tech: Python, PySpark, AWS, Iceberg/Kafka, Spark/Glue, CI/CD
Industry: Financial services / securities trading
Immersum continue to support a leading SaaS securities trading platform, who are hiring a Data Engineer to join a wider tech team of 25. You will be working on a blend of new and existing projects working with the latest tech in a greenfield large, highly scalable data lake environment.
The Company: For the past 20+ years they have been a leading SaaS platform providing a full product suite of services to the securities trading sector. They serve in excess of 150 financial institutions and support the majority of major global banks. As they continue to grow their services to their customers they have an exciting opportunity for their Data Engineer to join the company to help grow and shape this function in the long term.
The Role: The successful candidate will work across these areas:
- Owning the build and maintenance of their Lake house and being the 'go-to' Data person in the business.
- Working with stakeholders from across the business showing the possibilities that Data provides.
- Build and manage new and existing pipelines as new products and functions become available on the platform.
- Be comfortable or show an interest to learn CI/CD, IaC and Infra tooling using Terraform, Ansible and Jenkins whilst automating everything with Python.
Tech (experience in any listed is advantageous):
- Python
- Cloud: AWS
- Lake house: Apache Spark or AWS Glue
- Cloud Native storage: Iceberg, RDS, RedShift, Kafka
- IaC: Terraform, Ansible
- CI/CD: Jenkins, Gitlab
- Other platforms such as Databricks or Snowflake will be considered.
You will have a fantastic opportunity to lead the Data Engineering division whether you decide to take your career path in leadership or IC, both routes are equally valuable for this role. You will be joining at a time when Data is in its infancy and helping to scale and grow the Data platform and processes to better serve the business. You will be working with stakeholders across the business who are experts in their fields and you will be supporting them as the Data expert.
If this looks of interest please click apply to find out more!
At this time sponsorship is not on offer.
Senior Data Engineer in Worcester employer: Immersum
Contact Detail:
Immersum Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer in Worcester
✨Tip Number 1
Network like a pro! Reach out to people in the financial services sector, especially those working with data. Use LinkedIn to connect and engage with them; you never know who might have a lead on that Senior Data Engineer role.
✨Tip Number 2
Show off your skills! If you’ve got a portfolio of projects or contributions to open-source, make sure to highlight them in conversations. Demonstrating your experience with Python, AWS, and data pipelines can really set you apart.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge, especially around CI/CD and data lakes. Practise common interview questions and scenarios related to data engineering to show you’re ready to hit the ground running.
✨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 Senior Data Engineer in Worcester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the Senior Data Engineer role. Highlight your experience with Python, AWS, and any relevant data technologies to show us you’re the right fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about data engineering and how your background aligns with our needs. Share specific examples of projects you've worked on that relate to building scalable data lakes or pipelines.
Showcase Your Technical Skills: Don’t forget to mention your familiarity with tools like Apache Spark, Terraform, and CI/CD practices. We want to see how you can contribute to our tech stack and help us grow our data capabilities.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and get back to you quickly!
How to prepare for a job interview at Immersum
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, AWS, and Apache Spark. Brush up on your knowledge of Data Lakes and pipelines, as you’ll likely be asked to discuss how you’ve used these tools in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering and how you overcame them. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it clear how your contributions made a difference.
✨Understand the Business Context
Since this role is within financial services, it’s crucial to understand how data impacts decision-making in this sector. Familiarise yourself with the company’s products and the types of financial institutions they serve, so you can speak intelligently about how data can drive value.
✨Ask Insightful Questions
Prepare thoughtful questions to ask at the end of the interview. This could include inquiries about the team’s current projects, the company’s data strategy, or how they envision the Data Engineering division evolving. It shows your genuine interest and helps you assess if the role is right for you.