At a Glance
- Tasks: Develop and implement cutting-edge data solutions in a relaxed, innovative environment.
- Company: Join a well-funded fintech company revolutionising credit risk technology.
- Benefits: Competitive salary, flexible work options, and a chill dress code.
- Other info: Great opportunities for career growth and working with the latest tech.
- Why this job: Make a real impact with your programming skills while enjoying a vibrant workplace.
- Qualifications: Degree in a relevant field and experience with Python, SQL, and ETL processes.
The predicted salary is between 72000 - 88000 £ per year.
ETL Data Developer Fintech90,000 Plus Bens I am looking for a high quality Data Developer who has had some exposure to SQL to assist with core development of a proprietary technology.
Our client is well funded Techstar Risk Technology business based on the credit risk space.
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 those who are motivated by the sharp end of technology and the possibility of making serious money doing something you are passionate about.
Passionate about pioneering Risk Tech and leveraging big data in credit risk, you are looking for the opportunity to use your analytics and programming skills to shape the vision and the future of the organisation.
You excel in an open environment where you will have the flexibility to work in a way that suits you best.
With a passion for high-quality innovative businesses, you are experienced in working in multiple programming languages (including Python, R and SQL) and agile development methodologies.
Day to day the Data Engineer will: Work alongside the Risk and Analytics team to create and implement machine learning risk models and large scale data projects from inception to production Build high quality datasets from raw data using some of the latest tools and technologies Build and embed defined data models and data flows to the cloud Drive large batch, streaming and machine learning applications from design to production Contribute to the design, implementation and monitoring of our cloud data platform as well as innovative ways to ingest, process, store and analyse various data sources Contribute to automation in the CI/CD pipelines, infrastructure management and configuration Use various methods to transform raw data from multiple sources into useful data, improving quality, integrity and accessibility.
Develop and test architectures that enable data extraction and transformation for predictive modelling Automate any repeatable and error prone data integrations and data preparation flows Manipulating and cleaning data, fulfil daily ad-hoc data requests and troubleshoot difficult technical issues Data Engineers must have:2:1 or above Hons. degree or equivalent in mathematics, computer science or comparable scientific discipline.
Python Build ETL Pipelines (e. g., Airflow)Javascript Build and CI/CD tools Write SQL code Create and implementing Rest APIs GIT and GIT branching BI Tools such as Looker, Qlik, Power BI, Tableau Containerisation technologies Google Cloud Platform (GCP): Data manipulation/transfer modules Reporting, data warehousing, data science and quantitative analysis techniques.
Data warehousing, data modelling and the creation of meaningful data visualisations My client is based in Central London with Flex work from home.
ETL, Data, Python, Perl, Unix
ETL Data Developer 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 ETL Data Developer 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 ETL Data Developer 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
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We think you need these skills to ace ETL Data Developer 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.
