Hybrid Data Engineer: Python, Azure & LLMs for FinTech

Hybrid Data Engineer: Python, Azure & LLMs for FinTech

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Design and maintain scalable data pipelines using Python and LLMs.
  • Company: Fast-growing FinTech company based in London with a collaborative culture.
  • Benefits: Hybrid work arrangement, professional development, and innovative projects.
  • Other info: Exciting opportunities for career growth in a thriving industry.
  • Why this job: Join a dynamic team and shape the future of finance with cutting-edge technology.
  • Qualifications: Expertise in Python, data engineering, and familiarity with LLMs.

The predicted salary is between 60000 - 80000 Β£ per year.

Netrolynx AI in the United Kingdom is seeking a skilled Data Engineer to design and maintain scalable data pipelines. The role is pivotal in a fast-growing FinTech company based in London, requiring expertise in Python, data engineering, and LLMs.

The ideal candidate will join a collaborative team, ensuring data quality and effective integration of emerging technologies, all while enjoying a hybrid work arrangement that fosters professional development and innovation.

Hybrid Data Engineer: Python, Azure & LLMs for FinTech employer: Netrolynx AI

Netrolynx AI is an exceptional employer that champions innovation and professional growth within the dynamic FinTech landscape of London. With a strong emphasis on collaboration and a hybrid work model, employees benefit from a supportive culture that encourages skill enhancement and the integration of cutting-edge technologies. Joining our team means being part of a forward-thinking organisation that values your contributions and invests in your future.

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Contact Details:

Netrolynx AI Recruitment Team

We think you need these skills to ace Hybrid Data Engineer: Python, Azure & LLMs for FinTech

Python
SQL
Problem-Solving Skills
Data Engineering
Communication Skills
Data Pipeline Development
API Integration