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For Companies At a Glance
- Tasks: Design and maintain scalable data processing solutions using Databricks, Python, and AWS.
- Company: Global financial services leader based in Glasgow with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Transform data into actionable insights and make a real impact in the finance sector.
- Qualifications: Strong skills in SQL, Python, and data management required.
- Other info: Join a dynamic team and collaborate with cross-functional experts.
The predicted salary is between 48000 - 72000 £ per year.
A global financial services leader based in Glasgow is seeking a talented Software/Data Engineer to join their Capital Analytics team. In this role, you will design and maintain scalable data processing solutions utilizing Databricks, Python, and AWS.
Key responsibilities include:
- Implementing ETL pipelines
- Collaborating with cross-functional teams
- Ensuring data quality throughout processing phases
The ideal candidate will have strong skills in SQL, Python, and data management. Join the team and contribute to transforming data into actionable insights.
Lead Data Engineer - Pipelines & Analytics in Glasgow employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer - Pipelines & Analytics in Glasgow
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Databricks, Python, and AWS. This gives you a chance to demonstrate your expertise beyond the written application.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and data management skills. Practice common technical questions and be ready to discuss how you've implemented ETL pipelines in past roles.
✨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 about their job search.
We think you need these skills to ace Lead Data Engineer - Pipelines & Analytics in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Databricks, Python, and AWS. We want to see how your skills align with the role, so don’t be shy about showcasing your 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 engineering and how you can contribute to our Capital Analytics team. Let us know what excites you about transforming data into actionable insights.
Showcase Your Technical Skills: When filling out your application, be sure to mention your proficiency in SQL and data management. We’re looking for someone who can implement ETL pipelines effectively, so any examples of your past work will definitely catch our eye!
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 the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at J.P. Morgan
✨Know Your Tech Stack
Make sure you’re well-versed in Databricks, Python, and AWS. Brush up on your SQL skills too! Be ready to discuss how you've used these technologies in past projects, as this will show your practical experience and understanding.
✨Showcase Your ETL Expertise
Prepare to talk about your experience with ETL pipelines. Think of specific examples where you’ve designed or maintained these processes. Highlight any challenges you faced and how you overcame them, as this demonstrates problem-solving skills.
✨Collaboration is Key
Since the role involves working with cross-functional teams, be ready to share examples of how you’ve successfully collaborated with others. Discuss how you communicate technical concepts to non-technical stakeholders, as this shows your ability to bridge gaps.
✨Focus on Data Quality
Data quality is crucial in this role, so prepare to discuss your strategies for ensuring data integrity throughout processing phases. Share any tools or methodologies you’ve used to maintain high standards, as this will reflect your attention to detail.
