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- Tasks: Deliver data engineering for complex products, focusing on insights and analytics.
- Company: Transform, a forward-thinking company in London or Manchester.
- Benefits: 28 days holiday, birthday off, and a flexible benefits package.
- Other info: Dynamic environment with opportunities for professional growth.
- Why this job: Join an Agile squad and work on innovative AI-driven data platforms.
- Qualifications: Expertise in Azure/AWS Databricks, Azure Data Factory, and data lakes required.
The predicted salary is between 60000 - 80000 £ per year.
Transform is seeking a Senior Data Engineer in London or Manchester to join their Agile squad. The role involves delivering data engineering on complex products for insights and analytics.
Key responsibilities include:
- Managing quality outputs
- Working with diverse data sources
- Building data infrastructures
Applicants must have expertise in Azure/AWS Databricks, Azure Data Factory, and data lakes.
Benefits include:
- 28 days holiday
- Birthday off
- Flexible benefits package
Senior Data Engineer – AI-Driven Data Platforms in London employer: Transform
Contact Detail:
Transform Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer – AI-Driven Data Platforms in London
✨Tip Number 1
Network like a pro! Reach out to current employees at Transform on LinkedIn or attend industry meetups. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data engineering projects, especially those involving Azure/AWS Databricks and data lakes. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Get ready for technical interviews by brushing up on your data engineering concepts and problem-solving skills. We can even do mock interviews together 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 application to highlight how our experience aligns with the role at Transform.
We think you need these skills to ace Senior Data Engineer – AI-Driven Data Platforms in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure/AWS Databricks and Azure Data Factory. We want to see how your skills align with the role, so don’t be shy about showcasing your data engineering expertise!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about data engineering and how you can contribute to our Agile squad. Keep it engaging and relevant to the job description.
Showcase Your Projects: If you've worked on any complex data products or built data infrastructures, make sure to mention them. We love seeing real-world examples of your work that demonstrate your ability to manage quality outputs.
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 us!
How to prepare for a job interview at Transform
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Azure/AWS Databricks, Azure Data Factory, and data lakes. Be ready to discuss how you've used these technologies in past projects, as well as any challenges you faced and how you overcame them.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex data engineering problems. Think about the methodologies you used and the impact your solutions had on insights and analytics. This will demonstrate your ability to deliver quality outputs.
✨Understand Agile Methodologies
Since the role is within an Agile squad, be prepared to discuss your experience with Agile practices. Highlight how you've collaborated with cross-functional teams and adapted to changing requirements in previous roles.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions that show your interest in the company and the role. Inquire about their current projects, team dynamics, or how they measure success in data engineering. This shows you're genuinely interested and engaged.