Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the enterprise data platform, ensuring reliability and scalability for analytics.
- Company: A growing international SaaS business with a remote-first culture.
- Benefits: 26 days PTO, performance-based compensation reviews, and flexible working.
- Other info: Manage a Data Engineer and thrive in a dynamic, supportive environment.
- Why this job: Own a vital role in shaping data strategies and driving innovation.
- Qualifications: Strong experience in data engineering, Azure, and Databricks.
The predicted salary is between 70000 - 90000 £ per year.
A growing international SaaS business is seeking a Data Platform Lead to own their enterprise data platform, ensuring reliability and scalability while enabling analytics. This hands-on role requires strong experience in data engineering, particularly with Azure and Databricks, and includes managing a Data Engineer.
The company offers a remote-first working environment, 26 days PTO, and performance-based compensation reviews.
Remote Data Platform Lead — Azure/Data Lake + AI Readiness in London employer: ApprovalMax
Contact Detail:
ApprovalMax Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Data Platform Lead — Azure/Data Lake + AI Readiness in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects, especially those involving Azure and Databricks. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common data platform challenges and solutions. Be ready to discuss how you would ensure reliability and scalability in a hands-on role like this one.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to get noticed and shows you’re serious about joining our remote-first team. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Remote Data Platform Lead — Azure/Data Lake + AI Readiness in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure and Databricks. 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 passionate about data engineering and how you can contribute to our enterprise data platform. Keep it engaging and personal!
Showcase Your Leadership Skills: Since this role involves managing a Data Engineer, highlight any leadership experience you have. We’re looking for someone who can inspire and guide others, so share examples of how you've done this in the past.
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!
How to prepare for a job interview at ApprovalMax
✨Know Your Tech Inside Out
Make sure you brush up on your Azure and Databricks knowledge. Be ready to discuss specific projects where you've implemented these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Leadership Skills
Since this role involves managing a Data Engineer, be prepared to talk about your leadership style. Share examples of how you've successfully led teams or projects in the past, focusing on collaboration and mentorship.
✨Understand the Business Context
Research the company’s products and how they leverage data analytics. Being able to connect your technical skills to their business goals will show that you’re not just a techie but also understand the bigger picture.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Think of scenarios where you had to ensure data reliability and scalability, and be ready to explain your thought process and the outcomes.