Data Engineer – FinTech Company – Newcastle at Noir Consulting
NUT, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

10 Jun, 25

Salary

0.0

Posted On

10 Mar, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

DATA ENGINEER - FINTECH COMPANY - NEWCASTLE

(Tech Stack: Data Engineer, Databricks, Python, Azure, Power BI, AWS QuickSight, AWS, TSQL, ETL, Agile Methodologies)
I’m working with a leading Software House in the FinTech industry, based in Newcastle, who are looking to hire a talented Data Engineer. This is a fantastic opportunity to join a forward-thinking company where you’ll play a key role in developing and optimising their data platform.

WHY JOIN?

This is a great opportunity to work with cutting-edge technology in a thriving FinTech environment. You’ll be part of a talented and collaborative team, with plenty of opportunities for growth and career development.
If you’re a Data Engineer looking for your next challenge, I’d love to hear from you!
Location: Newcastle, UK
Salary: Competitive + Bonus + Pension + Benefits
Applicants must be based in the UK and have the right to work in the UK even though remote work is available.
To apply for this position please send your CV to Matt Jones at Noir.

Responsibilities

THE ROLE:

As a Data Engineer, you’ll be working closely with the front office to understand data needs and help shape the company’s data capabilities. You’ll be responsible for building and optimising data pipelines, automating data processes, and ensuring high data quality and governance.

KEY RESPONSIBILITIES:

  • Collaborate with the front office to scope and understand data requirements.
  • Build and maintain the data platform using in-house and third-party tools.
  • Automate data processes to improve efficiency and scalability.
  • Develop robust data pipelines to ingest and transform data from multiple providers.
  • Curate both external and internal datasets to meet business needs.
  • Design and implement best-practice data architecture and governance strategies.
  • Establish and maintain data quality standards and validation rules.
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