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- Tasks: Build automated data workflows and implement innovative data solutions.
- Company: Leading global organisation with a focus on data-driven decision-making.
- Benefits: Competitive salary, mentorship opportunities, and a dynamic work environment.
- Why this job: Join a team that values innovation and enhances your skills in data analytics.
- Qualifications: 5+ years in data engineering, advanced SQL and Python skills required.
- Other info: Agile environment with opportunities for career growth and mentoring.
The predicted salary is between 43200 - 72000 £ per year.
A leading global organisation seeks an experienced Analytics Engineer to join their London team. The ideal candidate will have over 5 years of experience in data and analytics engineering, along with advanced skills in SQL and Python. You will play a key role in building automated data workflows and implementing data solutions using technologies like Azure Databricks and Power BI. The role focuses on enhancing data-driven decision-making and mentoring junior team members within an agile environment.
Analytics Engineer: Data Platform & Self-Service Analytics employer: Stanton House
Contact Detail:
Stanton House Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Analytics Engineer: Data Platform & Self-Service Analytics
✨Tip Number 1
Network like a pro! Reach out to current employees at the company through LinkedIn or industry events. 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 best data workflows and analytics projects. We want to see how you’ve used SQL and Python to solve real problems, so make it shine!
✨Tip Number 3
Practice makes perfect! Get ready for those technical interviews by brushing up on your SQL queries and Python coding. We recommend doing mock interviews with friends or using online platforms to simulate the experience.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Analytics Engineer: Data Platform & Self-Service Analytics
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with SQL and Python in your application. We want to see how you've used these skills in real-world scenarios, especially in building automated data workflows.
Tailor Your Application: Don’t just send a generic application! Take the time to tailor your CV and cover letter to reflect the specific requirements of the Analytics Engineer role. We love seeing candidates who understand what we’re looking for.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and how it relates to the job.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to track your application and ensure it reaches the right people!
How to prepare for a job interview at Stanton House
✨Know Your Tech Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've used these technologies, especially in relation to Azure Databricks and Power BI. This will show that you not only understand the tools but can also apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've built automated data workflows in the past. Think of examples where you faced challenges and how you overcame them. This will demonstrate your analytical thinking and ability to enhance data-driven decision-making.
✨Mentorship Matters
Since the role involves mentoring junior team members, be ready to share your experiences in guiding others. Discuss your approach to mentorship and how you’ve helped others grow in their roles. This will highlight your leadership qualities and fit within an agile environment.
✨Cultural Fit is Key
Research the company culture and values of the organisation. Be prepared to discuss how your personal values align with theirs. Showing that you’re a good cultural fit can be just as important as your technical skills.
