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- Tasks: Lead the data architecture and manage a team while developing data pipelines.
- Company: Fast-growing SaaS company in Greater London with a dynamic work culture.
- Benefits: Competitive salary, 10% bonus, and opportunities for professional growth.
- Why this job: Shape the future of data and mentor a talented team in an innovative environment.
- Qualifications: Strong Python and SQL skills, plus experience with Azure cloud platforms.
- Other info: Hands-on role with excellent career advancement potential.
The predicted salary is between 48000 - 72000 £ per year.
A fast-growing SaaS company in Greater London is seeking a Lead Data Engineer to shape the data architecture and manage a team. This hands-on role involves overseeing the entire data lifecycle, mentoring team members, and developing data pipelines using Databricks, Spark, and Delta Lake.
Ideal candidates will have strong Python and SQL skills and experience with cloud platforms, ideally Azure. The position offers a competitive salary and a bonus of 10%.
Azure Data Platform Lead - Build Trusted Data & Pipelines employer: OpenSource
Contact Detail:
OpenSource Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Azure Data Platform Lead - Build Trusted Data & Pipelines
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Databricks, Spark, and Delta Lake. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and SQL skills. We recommend doing mock interviews with friends or using online platforms to get comfortable with common questions related to data architecture and pipeline management.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive and eager to join our team!
We think you need these skills to ace Azure Data Platform Lead - Build Trusted Data & Pipelines
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you’ve used these tools in real projects, especially with Azure, Databricks, or Spark.
Tailor Your Application: Don’t just send a generic CV! Tailor your application to reflect the job description. Mention your experience with data architecture and team management to show us you’re the right fit for this hands-on role.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication, so avoid jargon unless it’s relevant to the role. Make it easy for us to see your qualifications!
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 OpenSource
✨Know Your Tech Inside Out
Make sure you brush up on your Python, SQL, and Azure skills. Be ready to discuss how you've used Databricks, Spark, and Delta Lake in past projects. The more specific examples you can provide, the better!
✨Showcase Your Leadership Skills
Since this role involves mentoring a team, be prepared to share your experiences in leading projects or teams. Think of examples where you've successfully guided others or resolved conflicts.
✨Understand the Data Lifecycle
Familiarise yourself with the entire data lifecycle, from collection to processing and storage. Be ready to discuss how you would approach building trusted data pipelines and what best practices you follow.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's data strategy and team dynamics. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
