At a Glance
- Tasks: Design and manage large-scale data pipelines in AWS, focusing on real-time data.
- Company: Join a leading Fintech company disrupting wealth management with innovative software.
- Benefits: Remote work, relaxed atmosphere, competitive salary, and opportunities for professional growth.
- Other info: Enjoy a calm, open environment similar to Facebook or Google.
- Why this job: Be part of a tech-savvy team making a real impact in the financial sector.
- Qualifications: Experience in ETL processes, SQL, and data warehousing; Python knowledge preferred.
The predicted salary is between 60750 - 74250 £ per year.
ETL Data Engineer – Fintech Remote with occasional travel to the London Office.
Quant Capital is urgently looking for a Data Engineer to join our well-known Fintech50 client who produces software disrupting the wealth management market.
My client has dominated the domestic market with their Saa S offering and they are looking to replicate this success internationally, to do this they are investing heavily in technologists from software developers to Technical operations.
The development team works in a very agile fashion on 2 week sprints.
Most of the business is now focussed around AWS.
We are looking for someone who has a passion for realtime data, Day to Day the Data Engineer will: Design, build, monitor and manage large scale batch and streaming data pipelines in AWS cloud environment Data Analysis Reverse engineer existing SQL scripts Data modelling The Data Engineer Must have: Experience in building complex data pipelines/ETL/ELT scripts Extensive experience with SQLExperience with Data Warehouse databases like Snowflake/Redshift/ Big Query Experience with Python Preferably have some knowledge of AWS and components such as S3, Kinesis, DMS, SNS, Glue, Athena, RDSExperience with implementing Rest APIs.
Business Intelligence (BI) knowledge/experience Knowledge on tools like Terraform, Airflow, DBT and Harness Modern data engineering practises The environment is that of Facebook or Google, relaxed open with time to think and make the right decisions.
The atmosphere is calm and relaxed with an open dress code.
This is a role for technologists, those who are motivated by the sharp end of technology and the possibility of making serious money doing something you are passionate about.
My client is based in Central London but the role is remote for the immediate future.
ETL, DATA,, EC2, Dev Ops, Linux, AWS, Java, CLoudwatch Key Responsibilities/Duties
AWS Data Engineer 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 AWS Data Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Quant Capital!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like AWS Data Engineer at Quant Capital.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Quant Capital.
✨Apply Directly through Our Website
When you find a suitable opening like AWS Data Engineer at Quant Capital, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace AWS Data Engineer 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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Quant Capital, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
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!
✨Showcase Your Projects
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
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Quant Capital!
✨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.
