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- Tasks: Lead data transformation projects and optimise enterprise data systems in a dynamic banking environment.
- Company: Join a leading financial institution with a focus on innovation and data excellence.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Why this job: Shape the future of financial data and make impactful decisions in a collaborative team.
- Qualifications: Strong data analysis skills, advanced SQL, and experience with financial datasets required.
- Other info: Exciting role with potential for career advancement in a fast-paced industry.
The predicted salary is between 43200 - 72000 £ per year.
An opportunity for a data focused leader to shape and deliver a large scale financial data transformation programme supporting strategic decision making across a banking business. The role centres on building robust data pipelines, owning the data warehouse architecture, and ensuring high quality data to power reporting, analytics and insights. Must have a strong understanding of Front Office Trading and Front Office Data.
Responsibilities:
- Lead the design, build and optimisation of the enterprise data warehouse, including sourcing, validation, ingestion and data architecture.
- Develop and manage automated ETL pipelines and workflows for financial datasets.
- Integrate data warehouse outputs with Salesforce, PowerBI, pricing platforms and other analytical endpoints.
- Ensure accuracy, consistency and scalability of historic and current datasets and align them to evolving data models.
- Create detailed business requirements documentation that supports technology delivery teams.
- Support the build of new data models that power internal management information and AI aligned analytics.
- Collaborate with internal teams and external providers to improve data quality and streamline data delivery processes.
- Drive enhancements in data governance and act as subject matter expert for all data related topics.
- Maintain data quality and client hierarchy within Salesforce in partnership with client onboarding teams.
Requirements:
- Strong experience in data analysis and enterprise level data systems.
- Advanced SQL expertise with the ability to build complex queries and tables.
- Hands on experience managing ETL processes and working to tight project timelines.
- Must have strong knowledge of financial data, accounting principles and CIB business information frameworks.
- Experience working with large and complex datasets in a financial context.
- Proficient in Python and experienced with at least one major cloud data warehouse platform such as Snowflake.
- Experience working within a large financial institution and educated to degree level in a STEM field.
- Experience using Salesforce or similar CRM platforms.
- Excellent communication skills, proactive mindset and the ability to work independently and collaboratively.
No sponsorship available; applicants must have the right to work in the region.
Front Office Data Analyst in England employer: Nicoll Curtin
Contact Detail:
Nicoll Curtin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Front Office Data Analyst in England
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your data skills. We recommend using real-world examples from your experience to demonstrate your expertise.
✨Tip Number 3
Don’t just apply and wait! Follow up with recruiters after submitting your application through our website. A little nudge can show your enthusiasm and keep you on their radar.
✨Tip Number 4
Stay updated on industry trends and tools relevant to the Front Office Data Analyst role. This knowledge can give you an edge in interviews and help you connect with potential employers.
We think you need these skills to ace Front Office Data Analyst in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Front Office Data Analyst role. Highlight your experience with data analysis, SQL, and any relevant financial data projects. We want to see how your skills match 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 and how your background makes you a great fit for our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to mention your technical skills, especially in SQL, Python, and any cloud data platforms like Snowflake. We’re keen on seeing how you’ve used these tools in real-world scenarios, so give us the details!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come in through our own channels!
How to prepare for a job interview at Nicoll Curtin
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of financial data and Front Office Trading. Be prepared to discuss how you've managed large datasets in the past and how you can apply that experience to the role. Having specific examples ready will show your expertise.
✨Show Off Your SQL Skills
Since advanced SQL expertise is a must, practice building complex queries before the interview. You might be asked to solve a problem on the spot, so being comfortable with SQL syntax and logic will give you an edge.
✨Demonstrate Your ETL Experience
Be ready to talk about your hands-on experience with ETL processes. Share specific projects where you developed automated pipelines and workflows, and explain how you ensured data quality throughout the process.
✨Communicate Clearly and Confidently
Excellent communication skills are key for this role. Practice explaining technical concepts in simple terms, as you may need to collaborate with non-technical teams. Confidence in your delivery will make a great impression.
