Data Engineer – Fintech50 in London

Data Engineer – Fintech50 in London

London Full-Time 60750 - 74250 £ / year (est.) No working from home possible
Quant Capital

At a Glance

  • Tasks: Manage data cubes and collaborate with teams to present and utilise data effectively.
  • Company: Join a leading fintech firm known for disruptive payments technology.
  • Benefits: Competitive salary, top-notch training, and a casual startup atmosphere.
  • Other info: Exciting growth opportunities in a dynamic environment with a focus on web and ecommerce strategy.
  • Why this job: Be part of an innovative team shaping the future of payments technology.
  • Qualifications: 2+ years in Data Analysis/Engineering and experience with PostGreSQL.

The predicted salary is between 60750 - 74250 £ per year.

Quant Capital is urgently looking for a Data Engineer to join our high profile client.

Our client is a current member of the fintech50 and proud to be known as best in disruptive payments technology.

It is a truly cutting edge tech firm with 50 people and a dev team of 7.

This week they received a further $40 million investment and are hiring aggressively.

The atmosphere is casual with a startup feel although the business is the world’s largest dedicated payments business (in terms of tech and market share).

This role is expansionary due to a brand new international platform being created.

Currently a data warehouse and data cube are being built by an external company mainly using Post Gre SQL.

The Data Engineer will come in to manage this cube and work with internal business teams in presenting and using this data.

The role has 2 elements both data display and business side data / requirements gathering.

The role offers both the ability to work technically as well as work with the leadership team in shaping how the business uses data from its clients and the market.

The firm has ambitious plans over the next year so needs a Data Engineer who can truly use data for client benefit and internal marketing.

Data Engineers / Data Scientists must have: (Below also shows tech stack)Proven experience in a Data Analysis or Engineering 2 years plus commercial experience Post Gre SQLComp Sci or Similar Degree Ideally Mondrian or Psyks (MDX)Computer Science Background Exposure to OO programming or Scripting Linux Basic Comp Sci principles Experience of building / using a data warehouse / data cube This is a unique opportunity for someone to expand further into web and ecommerce strategy.

You should be driven and interested to gain some serious financial experience.

This is a bleeding edge business so if you can make a usability case they will buy it.

Flipflops and tshirts are perfectly normal for the office.

My client offers one of the best training and development packages in the market, all inclusive.

My client is based near Hammersmith Data Science, BI, SQL, Business Intelligence, SSIS SSRS, Data Warehousing, Business Analyst

Data Engineer – Fintech50 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.

Quant Capital

Contact Details:

Quant Capital Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Engineer – Fintech50 in London

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We think you need these skills to ace Data Engineer – Fintech50 in London

Python
SQL
Problem-Solving Skills
Communication Skills
Data Engineering
Automation
Data Governance

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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How to prepare for a job interview at Quant Capital

Brush Up on Your Statistics

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Get Comfortable with Python and R

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Prepare for Case Studies

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