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- Tasks: Build resilient Data Pipelines and manage complex financial datasets.
- Company: Leading financial services firm in Manchester with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Join a dynamic team and work on cutting-edge data solutions in finance.
- Qualifications: Experience in financial data, Python, Databricks, and a relevant degree.
- Other info: Exciting projects with potential for career advancement in a thriving sector.
The predicted salary is between 28800 - 48000 £ per year.
A leading financial services firm in Manchester is seeking an experienced Azure Data Engineer to build resilient Data Pipelines for complex projects in the Financial Services/Capital Markets sector. The role involves managing multi-source datasets and optimizing data ingestion processes.
Candidates should have experience in financial data domains, strong technical skills in Python and Databricks, and a degree in a related field. This position offers a chance to work on innovative data solutions.
Azure Data Engineer - Pipelines, Spark & Finance Data in Manchester employer: Arrow Global Group
Contact Detail:
Arrow Global Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Engineer - Pipelines, Spark & Finance Data in Manchester
✨Tip Number 1
Network like a pro! Reach out to professionals in the financial services sector on LinkedIn. Join relevant groups and engage in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Azure, Python, and Databricks. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions, especially those related to financial data. Practice explaining your thought process clearly and confidently.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to stay updated on new roles.
We think you need these skills to ace Azure Data Engineer - Pipelines, Spark & Finance Data in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure, Python, and Databricks. 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! Tell us why you’re passionate about data engineering in the financial sector and how your background makes you a perfect fit for our team.
Showcase Your Projects: If you've worked on any cool data pipelines or financial data projects, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions of your work.
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 Arrow Global Group
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in Python and Databricks. Be ready to discuss how you've used these tools in past projects, particularly in building data pipelines or optimising data ingestion processes.
✨Understand Financial Data Context
Since this role is in the financial services sector, it’s crucial to have a solid grasp of financial data domains. Familiarise yourself with common challenges and solutions in managing multi-source datasets within this industry.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems related to data pipelines. Think about specific examples from your experience where you successfully tackled similar challenges, and be ready to explain your thought process.
✨Showcase Your Innovative Side
This position offers a chance to work on innovative data solutions, so don’t shy away from sharing your ideas. Prepare to discuss any creative approaches you've taken in previous roles to enhance data processing or pipeline efficiency.