At a Glance
- Tasks: Design and build cloud-based data pipelines for advanced analytics and machine learning.
- Company: Dynamic financial services firm focused on innovation and collaboration.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a collaborative culture that values innovation and creativity.
- Why this job: Join a small, agile team and make a real impact in data engineering.
- Qualifications: Strong Python skills, Azure experience, and knowledge of Snowflake data warehousing.
The predicted salary is between 63000 - 77000 £ 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.
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Data Engineer - Azure Cloud Data Pipelines & ML in London employer: Cerberus Capital Management
At Cerberus Capital Management, we pride ourselves on being an exceptional employer that fosters innovation and collaboration in a dynamic environment. As a Production AI Engineer, you'll have the opportunity to work alongside talented professionals, driving impactful projects that enhance decision-making across our investment strategies. Our commitment to employee growth is reflected in our supportive culture and the resources we provide for continuous learning and development.
Contact Details:
Cerberus Capital Management Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Azure Cloud Data Pipelines & ML in London
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We think you need these skills to ace Data Engineer - Azure Cloud Data Pipelines & ML in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
