At a Glance
- Tasks: Design and build scalable Snowflake data models and pipelines for investment analytics.
- Company: Dynamic consultancy working with a boutique asset management firm in London.
- Benefits: Competitive daily rate, hybrid work model, and opportunity to shape data strategies.
- Other info: Join a forward-thinking team focused on eliminating data silos and enhancing operational efficiency.
- Why this job: Transform data processes and drive impactful investment decisions with cutting-edge technology.
- Qualifications: Experience in Snowflake, ELT/ETL workflows, and real-time data streaming.
Tired of untangling legacy data silos? Ready to build something that actually drives investment decisions? We are working with a London-based consultancy deployed at a boutique asset management firm. They aren't just moving data around; they are implementing Snowflake from the ground up to sharpen investment analytics, secure data sharing, and completely transform their operational efficiency. This is where you come in. You won't be babysitting old systems. You'll be designing the models and pipelines that make real-time data flow seamlessly.
What you’ll be doing:
- Designing, building, and maintaining scalable Snowflake data models and pipelines.
- Driving robust ELT/ETL workflows with a heavy focus on dbt.
- Implementing real-time or near real-time data streaming (using Kafka or Kinesis).
- Streamlining engineering processes to permanently eliminate data silos.
- Bonus: Integrating Aiviq native solutions (if you have this experience, we definitely want to talk to you).
Snowflake Data Engineer - Asset Management in London employer: Talenting Career Science
Join a forward-thinking consultancy that values innovation and collaboration, where your expertise as a Snowflake Data Engineer will directly impact investment decisions. With a hybrid working model in the heart of London, you'll enjoy a dynamic work culture that fosters professional growth and encourages you to take ownership of your projects. Benefit from competitive daily rates and the opportunity to work on cutting-edge data solutions that truly transform operational efficiency.
StudySmarter Expert Advice🤫
We think this is how you could land Snowflake Data Engineer - Asset Management in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the asset management and data engineering space. Attend meetups or webinars where you can chat with industry folks. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Snowflake projects, especially those involving ELT/ETL workflows. 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 technical knowledge. Be ready to discuss your experience with real-time data streaming and dbt. Practising common interview questions can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Snowflake Data Engineer - Asset Management in London
Some tips for your application 🫡
Show Your Passion for Data:When you're writing your application, let your enthusiasm for data engineering shine through. We want to see how excited you are about building scalable Snowflake models and transforming data processes. Share any relevant projects or experiences that highlight your passion!
Tailor Your CV and Cover Letter:Make sure to customise your CV and cover letter for this role. Highlight your experience with Snowflake, dbt, and any real-time data streaming tools like Kafka or Kinesis. We love seeing how your skills align with what we're looking for, so don’t hold back!
Be Clear and Concise:Keep your application clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Avoid jargon unless it’s relevant, and make sure we can easily see why you’re a great fit for the role.
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 shows us you’re serious about joining our team at StudySmarter!
How to prepare for a job interview at Talenting Career Science
✨Know Your Snowflake Inside Out
Make sure you brush up on your Snowflake knowledge before the interview. Understand its architecture, features, and how it integrates with ELT/ETL workflows. Be ready to discuss your past experiences with Snowflake and how you've used it to solve real-world problems.
✨Showcase Your Data Modelling Skills
Prepare to talk about your experience in designing and building data models. Bring examples of scalable models you've created and be ready to explain your thought process. Highlight any challenges you faced and how you overcame them, especially in relation to asset management.
✨Demonstrate Your Streaming Expertise
If you've worked with real-time data streaming using Kafka or Kinesis, make sure to mention it! Discuss specific projects where you implemented these technologies and the impact they had on data flow and operational efficiency. This will show that you can handle the demands of the role.
✨Be Ready for Problem-Solving Questions
Expect some scenario-based questions that test your problem-solving skills. Think about how you would approach eliminating data silos or streamlining engineering processes. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate your analytical thinking.
