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For Companies At a Glance
- Tasks: Design and optimise data products while collaborating with tech teams and Sales users.
- Company: Leading global finance institution with a focus on innovation.
- Benefits: Competitive salary, career progression to VP, and dynamic work environment.
- Why this job: Drive impactful data initiatives and enhance analytics capabilities in a thriving sector.
- Qualifications: Degree in Computer Science, strong Python skills, and data engineering experience.
- Other info: Join a team that values collaboration and offers excellent growth opportunities.
The predicted salary is between 54000 - 84000 £ 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 in London 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 in London
✨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! If you’ve got a portfolio of projects or contributions, make sure to highlight them during interviews. It’s all about proving you can walk the walk.
✨Tip Number 3
Prepare for those tricky questions! Brush up on your Python and data engineering concepts. We want you to feel confident when discussing how you’d tackle real-world challenges.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Lead Data Architect (Markets Sales) - Path to VP in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong Python skills and any relevant data engineering experience. We want to see how you can bring your technical expertise to the table!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect how your experience aligns with the Lead Data Architect role. We love seeing candidates who take the time to connect their background with our needs.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to understand and get straight to the point about your achievements.
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!
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 closely with technical teams and Sales users, prepare examples that highlight your ability to collaborate effectively. Think of situations where you’ve successfully bridged the gap between technical and non-technical stakeholders.
✨Prepare for Technical Questions
Expect to face technical questions that assess your data engineering background. Review common data architecture challenges and be ready to discuss how you would approach designing sales data products or optimising data architectures.
✨Demonstrate Impactful Initiatives
Be prepared to talk about past projects where you drove impactful data initiatives. Highlight how your contributions enhanced analytics capabilities and improved data quality, as this will resonate well with the interviewers.
