At a Glance
- Tasks: Build and maintain data pipelines on AWS, driving cloud transformation in investment banking.
- Company: Established Japanese investment bank with a focus on capital markets.
- Benefits: Competitive daily rate of £700, hybrid work model, and hands-on experience.
- Other info: Opportunity to mentor others and grow in a fast-paced, innovative environment.
- Why this job: Join a dynamic team to make a real impact on data engineering and cloud solutions.
- Qualifications: 5+ years AWS engineering experience, strong Python skills, and data engineering fundamentals.
The predicted salary is between 63000 - 77000 £ per year.
A well-established Japanese investment bank operating in capital markets is bringing in a hands-on Data Platform Engineer to help drive its AWS cloud transformation programme. This is a genuine build-and-run role for someone who's happiest with their hands on the keyboard, not just steering from the sidelines.
You'll be joining the Applications team to build and operate data pipelines and integration flows across front and back office systems, combining data engineering with platform engineering to deliver production-ready services. Expect a mix of hands-on AWS delivery (Glue, Lambda, Step Functions, EventBridge) and closer collaboration with the architecture team to keep implementation aligned with strategic direction.
What You'll Be Doing
- Building and maintaining data pipelines and integration flows (batch and near real-time) across the Applications landscape
- Delivering cloud-based data solutions on AWS aligned to architectural standards and the cloud transformation programme
- Implementing scalable, resilient data processing patterns, including event-driven data flows
- Working with messaging/streaming technologies to support data movement across systems
- Supporting platform reliability - monitoring, alerting, and performance optimisation
- Contributing to CI/CD, automation, and infrastructure-as-code for consistent, efficient delivery
- Mentoring and upskilling team members to embed sustainable ways of working
What We're Looking For
- Minimum 5 years' hands-on AWS engineering experience, ideally in data engineering, cloud platform engineering, or enterprise application integration
- Strong hands-on experience with AWS data platform services: Glue, Lambda, Step Functions, EventBridge, S3, Athena, RDS, Lake Formation, IAM, CloudWatch
- Strong Python development skills for Glue jobs, Lambda functions, and automation/integration workflows
- Practical experience with Terraform as primary IaC tool, plus CI/CD tooling (Bitbucket Pipelines, GitHub Actions, or GitLab CI)
- Solid data engineering fundamentals - SQL, data modelling, pipeline design, batch and near-real-time flows
- Experience with messaging/streaming/event-driven architectures (ActiveMQ/Artemis, RabbitMQ, or AWS Kinesis)
- Experience with containerised/compute platforms - Amazon EKS and EC2
Desirable
- AWS Certified Solutions Architect, Developer, or Data Engineer (or equivalent Azure/GCP with strong AWS delivery background)
- Experience with QuickSight, AWS Bedrock, or Bedrock AgentCore
- Background in financial services / capital markets or another regulated, data-heavy environment
AWS Data Engineer - Inside IR35 - Investment Banking in London employer: SRG Careers
Join a forward-thinking company in Darlington that values innovation and employee development. As a Maintenance Team Leader, you'll benefit from a competitive salary, a supportive work culture that encourages continuous improvement, and opportunities for professional growth within cutting-edge laboratory and manufacturing environments. This role not only allows you to lead a dedicated team but also keeps you engaged with hands-on technical challenges, making it an ideal place for those seeking meaningful and rewarding employment.
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We think this is how you could land AWS Data Engineer - Inside IR35 - Investment Banking in London
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We think you need these skills to ace AWS Data Engineer - Inside IR35 - Investment Banking in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at SRG Careers, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SRG Careers. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at SRG Careers
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SRG Careers!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
