At a Glance
- Tasks: Join a prestigious firm as a Cloud Data Engineer, driving innovative cloud solutions.
- Company: Renowned quantitative trading firm with a focus on cutting-edge technology.
- Benefits: Competitive salary, bonuses, and a dynamic work environment.
- Other info: Work in a startup-like atmosphere with excellent learning opportunities.
- Why this job: Make an impact in a tech-driven culture while collaborating with top talent.
- Qualifications: 5+ years AWS experience and strong coding skills required.
The predicted salary is between 63000 - 77000 £ per year.
Cloud Data Engineer Hybrid130,000-160,000 + benefits and bonus Quant Capital is urgently looking for a Cloud Data Engineer to join our high profile client.
My client is a prestigious quantitative trading firm renowned for combining cutting-edge technology with exceptional talent, my client operates globally in various markets.
They embrace autonomy and agility, allowing them to seize opportunities by trading with internal capital and assuming their own risks.
We are currently seeking a talented Cloud Engineer to join my client’s Core Infrastructure Services team.
In this role, you will collaborate with various teams across the firm to empower engineers in exploring firmwide solutions for quantitative engineering and research.
You will play a vital role in establishing and building an infrastructure-as-code (IAC) repository while maintaining responsive communication with teammates.
Collaboration with information security and infrastructure colleagues will be essential.
Responsibilities: Oversee multiple AWS environments, promoting collaboration among teams and providing support for their development initiatives.
Integrate services and access routes within a data-intensive hybrid cloud environment.
Develop, enhance, and fully automate CI/CD development cycles.
Gather business and technical requirements to propose solutions that consolidate data management under a unified structure across the organization.
Offer recommendations and create illustrative examples of hybrid cloud technology solutions for data engineering.
Stay up-to-date with the latest advancements in cloud technology, services, and networking.
Evaluate vendor solutions, generate recommendations, and deliver internal training to clients.
Requirements: Bachelor’s degree in a STEM field5+ years of experience working with Amazon Web Services (AWS), including exposure to other cloud vendors In-depth understanding of AWS’s suite of tools and services for data management and pipelining, including VPC, EMR, S3, RDS, Kinesis, Glue, Redshift, and Data Pipeline.
Proficiency in infrastructure-as-code tools such as Terraform, Cloud Formation, and related technologies.
Strong knowledge of Kubernetes.
Proficiency in at least one back-end programming language, such as Python or Go.
Expertise in constructing highly available and fault-tolerant big data environments in the cloud, utilizing No SQL and RDMS technologies like Hadoop, Spark, Postgre SQL, and cloud-based management tools such as EMR, Athena, and RDS.
Ability to implement systems with a security-first mindset, adhering to firm-wide security policies and utilizing cloud-based security tools like IAM and KMS.
Working knowledge of cloud-based data analytics solutions, such as Databricks and Snowflake.
This is an environment akin to a well-funded Fin Tech startup where tech is number 1 with a big budget allocated towards technology.
The firm is known globally for its attitudes and rigour more importantly, you will be surrounded by smart people deeply interested learning and in teaching what they know, as well as learning from you.
My client is based in London
Cloud Data Engineer – Quanttrading in London employer: Quant Capital
Quant Capital is an excellent employer for those looking to thrive in the fintech sector, offering a vibrant work culture that fosters innovation and collaboration. With substantial training and development opportunities, employees can enhance their skills while enjoying a flexible hybrid work model in the heart of London. Join us to be part of a forward-thinking team that values growth and cutting-edge technology.
StudySmarter Expert Advice🤫
We think this is how you could land Cloud Data Engineer – Quanttrading in London
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We think you need these skills to ace Cloud Data Engineer – Quanttrading 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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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Quant Capital. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Quant Capital
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
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✨Prepare for Case Studies
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.
