Hybrid Data Engineer: Real-Time Pipelines & Analytics

Hybrid Data Engineer: Real-Time Pipelines & Analytics

Full-Time 50000 - 65000 Β£ / year (est.) No working from home possible
Tain

At a Glance

  • Tasks: Build scalable data pipelines and ensure data accuracy for analytics.
  • Company: Join Tain, a forward-thinking company in the heart of Greater London.
  • Benefits: Enjoy competitive salary, hybrid work, and great benefits.
  • Other info: Dynamic role with opportunities for growth in a tech-driven environment.
  • Why this job: Make an impact by working on real-time data solutions and analytics.
  • Qualifications: Experience in data engineering and strong collaboration skills.

The predicted salary is between 50000 - 65000 Β£ per year.

The Data Engineer at Tain is responsible for building scalable data pipelines and infrastructure powering analytics across the organisation.

You will ensure data accuracy and timeliness in high-volume transactional and API-driven environments.

Collaborating with Data Architect and Analysts, you will design ETL/ELT processes, integrate APIs, and implement monitoring, validation, and cost-efficient pipelines.

Hybrid work in Greater London is offered along with competitive salary and benefits.

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Hybrid Data Engineer: Real-Time Pipelines & Analytics employer: Tain

Tain is an exceptional employer that champions flexibility and work-life balance, offering a remote working environment that allows you to thrive in your role as a Financial Controller. With opportunities for professional growth and direct collaboration with senior leadership, you will be part of a dynamic team driving innovation in the tech sector. The company's commitment to employee development and its vibrant culture make it an ideal place for those seeking meaningful and rewarding employment.

Tain

Contact Details:

Tain Recruitment Team

We think you need these skills to ace Hybrid Data Engineer: Real-Time Pipelines & Analytics

SQL
Python
Communication Skills
Data Pipeline Development
Problem-Solving Skills
Automation
Data Engineering