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- Tasks: Build resilient data pipelines for complex financial datasets using Azure technologies.
- Company: Join Arrow, a leading player in the financial services sector.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and development.
- Other info: Full-time permanent role with a focus on innovation and collaboration.
- Why this job: Make an impact in finance by leveraging your data engineering skills.
- Qualifications: Experience with Azure Data Factory and Databricks; analytical mindset required.
The predicted salary is between 45000 - 55000 £ per year.
Arrow is seeking a skilled Data Engineer in Manchester to join their IT & Change department. The role focuses on building resilient and reusable Data Pipelines for complex datasets within financial services.
Candidates should have experience with Azure Data Factory, Databricks, and a background in financial data. A degree in a relevant field is preferable, along with strong analytical and communication skills.
This is a full-time permanent position offering a dynamic working environment.
Azure Data Engineer – Pipelines & Analytics for Finance in Manchester employer: Arrow
Contact Detail:
Arrow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Engineer – Pipelines & Analytics for Finance in Manchester
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and data engineering sectors on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your previous projects, especially those involving Azure Data Factory and Databricks. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions related to data engineering and financial datasets to boost your confidence.
✨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 ensure your application gets seen by the right people.
We think you need these skills to ace Azure Data Engineer – Pipelines & Analytics for Finance in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure Data Factory and Databricks. We want to see how your skills align with the role, so don’t be shy about showcasing your financial data background!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering in finance and how you can contribute to our team. Keep it engaging and relevant to the job description.
Show Off Your Analytical Skills: Since this role requires strong analytical skills, consider including specific examples of how you've tackled complex datasets in the past. We love seeing real-world applications of your expertise!
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 from our team!
How to prepare for a job interview at Arrow
✨Know Your Azure Tools
Make sure you brush up on your knowledge of Azure Data Factory and Databricks. Be ready to discuss how you've used these tools in past projects, especially in the context of building data pipelines for financial datasets.
✨Showcase Your Analytical Skills
Prepare to demonstrate your analytical thinking. Think of specific examples where you've tackled complex data challenges, particularly in finance. This will show that you can handle the intricacies of the role.
✨Communicate Clearly
Strong communication skills are key in this role. Practice explaining technical concepts in simple terms, as you may need to collaborate with non-technical stakeholders. Clear communication can set you apart from other candidates.
✨Research Arrow's Culture
Take some time to understand Arrow's values and work culture. Being able to align your answers with their mission and demonstrate how you'd fit into their dynamic environment can make a big difference in your interview.