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- Tasks: Design and build cloud-based data pipelines using Azure and modern tools.
- Company: Dynamic financial services firm focused on innovation and collaboration.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Join a small, agile team and make a real impact in data analytics and machine learning.
- Qualifications: Strong Python skills, Azure experience, and knowledge of data warehousing with Snowflake.
- Other info: Exciting environment with a focus on advanced analytics and machine learning.
The predicted salary is between 50000 - 70000 £ per year.
A financial services firm is seeking a Data Engineer to expand their capabilities in building modern, scalable data platforms. The role involves designing cloud-based data pipelines and utilizing tools such as dbt and Airflow.
The ideal candidate will possess strong Python skills, experience with Azure, and an understanding of data warehousing with Snowflake.
This position provides opportunities for impact within a small, agile team dedicated to optimizing data for advanced analytics and machine learning applications, promoting a collaborative and innovative culture.
Data Engineer - Azure Cloud Data Pipelines & ML in London employer: Cerberus Capital Management
Contact Detail:
Cerberus Capital Management Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Azure Cloud Data Pipelines & ML in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working with Azure and data pipelines. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with dbt, Airflow, and Python. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of data warehousing and machine learning applications. Be ready to discuss how you've optimised data in past roles and how you can contribute to their agile team.
✨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 about their job search.
We think you need these skills to ace Data Engineer - Azure Cloud Data Pipelines & ML in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Azure, Python, and data warehousing. We want to see how your skills align with the role of a Data Engineer, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about building scalable data platforms and how you can contribute to our innovative culture. Let us know what excites you about this opportunity!
Showcase Your Technical Skills: When applying, make sure to mention your experience with tools like dbt and Airflow. We’re looking for someone who can hit the ground running, so any specific examples of your work with these tools will definitely catch our eye.
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 Cerberus Capital Management
✨Know Your Tech Stack
Make sure you’re well-versed in Azure, dbt, and Airflow. Brush up on your Python skills too! Be ready to discuss how you've used these tools in past projects, as this will show your practical experience and understanding of the tech stack.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data engineering and how you overcame them. Think about examples where you optimised data pipelines or improved data quality, as this will highlight your analytical thinking and ability to innovate.
✨Understand Data Warehousing Concepts
Familiarise yourself with Snowflake and its features. Be prepared to explain how you would design a data warehouse and the benefits it brings to advanced analytics and machine learning applications. This shows you’re not just a coder but also a strategic thinker.
✨Emphasise Team Collaboration
Since the role involves working within a small, agile team, be ready to share experiences where you collaborated effectively with others. Highlight your communication skills and how you contribute to a positive team culture, as this is key for their innovative environment.