At a Glance
- Tasks: Support liquidity reporting and enhance data capabilities using SQL.
- Company: Join a global workforce solutions partner committed to inclusivity and innovation.
- Benefits: Hybrid work model, competitive pay, and opportunities for professional growth.
- Other info: Dynamic role with exposure to advanced data technologies and BI tools.
- Why this job: Make an impact in banking by modernising liquidity data and reporting processes.
- Qualifications: Strong SQL skills and experience in liquidity reporting or financial services.
The predicted salary is between 50000 - 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 Liquidity Data Analyst (SQL) for a 6 Months contract based in London (Hybrid - 3 times per week in the office).
Purpose of the role: As Liquidity Data Analyst you will support the modernisation of liquidity reporting and data capabilities. This role sits at the intersection of liquidity risk, regulatory reporting, and advanced data analytics, with a strong focus on enhancing data structures, improving reporting accuracy, and evolving the liquidity data dictionary.
What you'll do:
- Support the production and optimisation of liquidity and regulatory reporting.
- Develop and maintain SQL-based datasets and pipelines for accurate liquidity data reporting.
- Analyse liquidity data to perform trend analysis, variance analysis, and root cause investigations.
- Contribute to the modernisation of liquidity data infrastructure and reporting processes.
- Build and enhance the liquidity data dictionary, ensuring strong data definitions, lineage, and governance.
The skills you'll need:
- Strong experience in liquidity reporting within banking or financial services.
- Advanced SQL skills and experience working with complex financial datasets.
- Proven background in data analysis, data modelling, and reporting.
- Understanding of data governance, data dictionaries, and data lineage concepts.
- Experience with BI tools such as Power BI or Tableau.
- Exposure to modern data platforms or technologies (e.g., Azure, Databricks, Snowflake, Python, or AI/analytics tools).
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.
Liquidity Data Analyst (SQL) employer: AMS CWS
AMS is an exceptional employer that prioritises inclusivity and employee growth, making it an ideal place for a Liquidity Data Analyst to thrive. With a strong focus on modernising liquidity reporting within a major UK retail bank, employees benefit from a dynamic work culture that encourages collaboration and innovation, alongside opportunities for professional development in a hybrid working environment in London. Joining AMS means being part of a forward-thinking team dedicated to optimising diverse talent strategies and enhancing data capabilities.
StudySmarter Expert Advice🤫
We think this is how you could land Liquidity Data Analyst (SQL)
✨Tip Number 1
Network like a pro! Reach out to people in the banking and financial services sector, especially those who work with liquidity data. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your SQL skills! If you get the chance, demonstrate your SQL prowess during interviews or networking events. Maybe even prepare a mini-project that showcases your ability to handle complex financial datasets.
✨Tip Number 3
Stay updated on industry trends! Follow relevant blogs, podcasts, or LinkedIn influencers in the banking and data analytics space. This knowledge can give you an edge in conversations and interviews.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always looking for talented individuals like you to join our team!
We think you need these skills to ace Liquidity Data Analyst (SQL)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Liquidity Data Analyst role. Highlight your SQL skills and any relevant experience in liquidity reporting or data analysis. We want to see how your background aligns 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 this role and how your skills can contribute to modernising liquidity reporting. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills:Don’t forget to mention your experience with BI tools like Power BI or Tableau, and any exposure to modern data platforms. We’re keen on seeing how you can leverage these tools to enhance our data capabilities.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any updates from us. Let’s get started!
How to prepare for a job interview at AMS CWS
✨Know Your SQL Inside Out
Make sure you brush up on your SQL skills before the interview. Be prepared to discuss complex queries and how you've used SQL in past projects, especially in relation to liquidity reporting. Practising some real-world scenarios can really help you stand out.
✨Understand Liquidity Reporting
Familiarise yourself with the key concepts of liquidity risk and regulatory reporting. Being able to articulate how these areas intersect with data analytics will show that you’re not just a tech whiz but also understand the financial context of your work.
✨Showcase Your Data Analysis Skills
Prepare examples of how you've performed trend analysis or variance analysis in previous roles. Highlight any specific tools or methodologies you used, and be ready to discuss the outcomes of your analyses and how they impacted decision-making.
✨Get Comfortable with BI Tools
If you have experience with Power BI or Tableau, make sure to mention it! Be ready to discuss how you've used these tools to enhance reporting processes. If you’ve worked with modern data platforms like Azure or Snowflake, don’t forget to bring that up too!
