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- Tasks: Define data products and optimise data architectures for impactful sales initiatives.
- Company: Leading global finance institution with a focus on innovation.
- Benefits: Competitive salary, career progression to VP, and collaborative work environment.
- Why this job: Join a dynamic team to enhance analytics capabilities and drive data initiatives.
- Qualifications: Degree in Computer Science, strong Python skills, and data engineering experience.
- Other info: Exciting opportunity for growth in a fast-paced financial sector.
The predicted salary is between 48000 - 72000 £ per year.
A leading global finance institution is seeking a Lead Data Architect for the Markets Sales CDAO team in London. The successful candidate will define data products, ensure data quality, and collaborate with both technical teams and Sales users.
Responsibilities include:
- Designing sales data products
- Optimizing data architectures
Qualifications include:
- A degree in Computer Science or related field
- Strong Python skills
- A data engineering background
Join to drive impactful data initiatives and enhance analytics capabilities.
Lead Data Architect (Markets Sales) - Path to VP employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Architect (Markets Sales) - Path to VP
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and data architecture space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data products and projects. This is your chance to demonstrate your Python prowess and data engineering expertise.
✨Tip Number 3
Prepare for those interviews! Research the company’s data initiatives and think about how you can contribute. Tailor your answers to highlight your experience with sales data products.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Lead Data Architect (Markets Sales) - Path to VP
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data architecture and engineering. We want to see how your skills in Python and your background align with the role, so don’t hold back on showcasing relevant projects!
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 you can contribute to our Markets Sales team. Let us know what excites you about this opportunity!
Showcase Your Collaboration Skills: Since this role involves working closely with technical teams and Sales users, highlight any past experiences where you’ve successfully collaborated across different departments. We love seeing teamwork in action!
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’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at J.P. Morgan
✨Know Your Data Inside Out
Make sure you’re well-versed in data architecture principles and the specific data products relevant to the finance sector. Brush up on your Python skills and be ready to discuss how you've used them in past projects, especially in relation to sales data.
✨Showcase Collaboration Skills
Since the role involves working with both technical teams and Sales users, prepare examples that highlight your ability to communicate complex data concepts clearly. Think of times when you’ve successfully collaborated across departments to drive a project forward.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions about data quality and architecture optimisation. Review common data engineering challenges and be ready to share your strategies for overcoming them. This will show your problem-solving skills and expertise.
✨Demonstrate Impactful Initiatives
Be prepared to discuss past projects where you’ve driven impactful data initiatives. Highlight how your contributions enhanced analytics capabilities and led to better decision-making. This will illustrate your potential value to the team.
