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- Tasks: Transform data into actionable insights and develop robust data pipelines.
- Company: Join a global workforce solutions partner committed to inclusivity and innovation.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Why this job: Make a real impact in banking by analysing customer behaviour and driving strategic decisions.
- Qualifications: Experience in data analysis, Python, Snowflake, and big data environments required.
- Other info: Work with a major UK retail bank and enjoy a dynamic, collaborative environment.
The predicted salary is between 36000 - 60000 £ per year.
AMS is a global workforce solutions partner committed to creating inclusive, dynamic, and future-ready workplaces. We help organisations adapt, grow, and thrive in an ever-evolving world by building, shaping, and optimising diverse talent strategies.
Our client, a major UK retail bank, provides everyday banking services to over 17 million retail customers. The bank's expertise and services span across Business Services, Corporate Banking, Wealth Management, Group Functions, Retail and Investment Banking.
On behalf of this organisation, AMS are looking for a Senior Data Analyst (Python - Snowflake) for a 6-month contract based in London (Hybrid - 2 times per week in the office).
Purpose of the role:
We are looking for an experienced Senior Data Analyst to join our Client's Balance Sheet Management team. This role is critical in delivering enhanced, granular insights into customer behaviour through enriched, application-level data. You will extract and transform data into actionable insights that support decision-making and operational improvements.
What you'll do:
- Develop and maintain a single source of enriched application-level data to be used across Finance, Treasury, Pricing function.
- Design and implement robust data pipelines leveraging existing data feeds from Pricing, Finance, and the PI CoE.
- Translate complex business requirements into scalable and maintainable code using Python, PySpark, and CI/CD best practices.
- Provide actionable insights into customer behaviours including Hopping, drawdown patterns, speed to Drawdown.
- Enable strategic and operational decision-making through accurate, timely, and behavioural insights.
- Work closely with stakeholders to inform business responses to emerging customer trends.
The skills you'll need:
- Proven experience as a Data Analyst or Data Engineer within the banking or financial services sector.
- Strong programming skills in Python, Snowflake and PySpark with experience in building reusable analytics libraries.
- Hands-on experience working in big data environments and on application-level datasets.
- Solid understanding of CI/CD processes, version control (e.g., Git), and deployment pipelines.
- Experience with interest rate risk management and understanding of treasury/ALM functions.
This client will only accept workers operating via an Umbrella or PAYE engagement model. If you are interested in applying for this position and meet the criteria outlined above, please click the link to apply and we will contact you with an update in due course.
Senior Data Analyst (Python - Snowflake) in London employer: Contingent Workforce Solutions
Contact Detail:
Contingent Workforce Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst (Python - Snowflake) in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the banking and financial services sector. Let them know you're on the lookout for a Senior Data Analyst 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! Create a portfolio showcasing your Python and Snowflake projects. This is your chance to demonstrate how you've turned complex data into actionable insights. Share it during interviews or even on LinkedIn to catch the eye of recruiters.
✨Tip Number 3
Prepare for those interviews! Research common questions for data analyst roles, especially around Python, PySpark, and CI/CD processes. Practise your answers and be ready to discuss how you've tackled real-world problems with data.
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, applying directly gives you a better chance of being noticed by hiring managers who are looking for someone just like you.
We think you need these skills to ace Senior Data Analyst (Python - Snowflake) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Analyst role. Highlight your experience with Python, Snowflake, and any relevant projects that showcase your skills in data analysis and engineering.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share specific examples of how you've used data to drive insights and decision-making in previous positions.
Showcase Your Technical Skills: Don’t forget to mention your programming skills and experience with CI/CD processes. We want to see how you’ve applied these in real-world scenarios, especially in banking or financial services.
Apply Through Our Website: To make sure your application gets noticed, apply directly through our website. This way, we can easily track your application and get back to you with updates!
How to prepare for a job interview at Contingent Workforce Solutions
✨Know Your Tech Inside Out
Make sure you brush up on your Python, Snowflake, and PySpark skills. Be ready to discuss specific projects where you've used these technologies, and think about how you can explain complex concepts in a simple way. This will show that you not only know your stuff but can also communicate effectively.
✨Understand the Business Context
Familiarise yourself with the banking sector, especially around balance sheet management and customer behaviour insights. Research the client’s services and think about how your role as a Senior Data Analyst can impact their operations. This knowledge will help you answer questions more effectively and demonstrate your genuine interest.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve hypothetical problems or describe how you would handle certain situations. Think of examples from your past experience where you’ve successfully extracted and transformed data into actionable insights. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Engage with Stakeholders
Since the role involves working closely with stakeholders, be prepared to discuss how you’ve collaborated with different teams in the past. Highlight your communication skills and how you’ve translated complex data into insights that drive decision-making. This will show that you’re not just a tech whiz but also a team player.
