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- Tasks: Design and develop data engineering solutions using Python/PySpark and Azure technologies.
- Company: A national law firm committed to diversity and inclusion.
- Benefits: 25 days holiday, flexible pension schemes, and well-being initiatives.
- Why this job: Join a supportive team and enhance data value creation in an aspirational culture.
- Qualifications: Experience with Python/PySpark and Azure Data Factory is essential.
- Other info: 12-month fixed-term role with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A national law firm is seeking a Data Engineer for a 12-month fixed-term role to enhance data value creation. The ideal candidate will design and develop data engineering solutions using Python/PySpark, Azure Data Factory, and Azure Databricks.
Benefits include:
- 25 days holiday
- Flexible pension schemes
- Well-being initiatives
You will be part of a supportive team that values diversity and inclusion while contributing to an aspirational data culture.
Data Engineer - Azure PySpark & Lakehouse (12m FTC) employer: Irwin Mitchell LLP
Contact Detail:
Irwin Mitchell LLP Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Azure PySpark & Lakehouse (12m FTC)
✨Tip Number 1
Network like a pro! Reach out to current or former employees of the firm on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a mini-project or a portfolio showcasing your work with Python, PySpark, and Azure. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get comfortable with common interview questions for data engineers. We can even do mock interviews with friends to boost our confidence.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can tailor our CV and cover letter to match the job description perfectly.
We think you need these skills to ace Data Engineer - Azure PySpark & Lakehouse (12m FTC)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, PySpark, and Azure. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this Data Engineer role and how you can contribute to our data culture. Keep it engaging and personal – we love to see your personality!
Showcase Your Problem-Solving Skills: In your application, highlight specific examples where you've tackled data challenges using Azure Data Factory or Databricks. We’re keen to see how you approach problems and create solutions that add value.
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. Plus, we love seeing applications come in through our own platform!
How to prepare for a job interview at Irwin Mitchell LLP
✨Know Your Tech Stack
Make sure you’re well-versed in Python, PySpark, Azure Data Factory, and Azure Databricks. Brush up on your technical skills and be ready to discuss how you've used these tools in past projects. Being able to share specific examples will show your expertise and confidence.
✨Understand the Company Culture
Research the law firm’s values, especially their focus on diversity and inclusion. Be prepared to discuss how you can contribute to a supportive team environment. Showing that you align with their aspirational data culture can set you apart from other candidates.
✨Prepare for Scenario-Based Questions
Expect questions that ask you to solve real-world problems using your data engineering skills. Practice articulating your thought process clearly and logically. This will demonstrate not only your technical abilities but also your problem-solving approach.
✨Ask Insightful Questions
Prepare thoughtful questions about the role and the team dynamics. Inquire about the current data projects or challenges they face. This shows your genuine interest in the position and helps you assess if it’s the right fit for you.
