Meter Data Specialist - Hybrid Role in Energy Market Ops in Leeds

Meter Data Specialist - Hybrid Role in Energy Market Ops in Leeds

Leeds Full-Time 45000 - 55000 Β£ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Ensure metering data accuracy and compliance while supporting customers and market operations.
  • Company: Join ENGIE UK, a leader in the energy sector with a focus on innovation.
  • Benefits: Enjoy a hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Dynamic role with opportunities for site travel and career advancement.
  • Why this job: Make a real impact in the energy market while collaborating with diverse teams.
  • Qualifications: Strong attention to detail and teamwork skills are essential.

The predicted salary is between 45000 - 55000 Β£ per year.

ENGIE UK is seeking a Meter Data Management Administrator to join our UK Energy Supply team.

Hybrid role based from Leeds, combining remote work with site travel.

You will ensure metering data accuracy and compliance, supporting customers and industry performance.

You will handle data flows, resolve discrepancies, manage MPRN activities, and support market operations with a right-first-time mindset and strong collaboration across teams.

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Meter Data Specialist - Hybrid Role in Energy Market Ops in Leeds employer: ENGIE UK

ENGIE UK is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. With a strong focus on employee growth, you will have access to cutting-edge technology and the opportunity to lead AI-driven initiatives that shape the future of energy management. The hybrid working model ensures a healthy work-life balance while being part of a forward-thinking team dedicated to making a meaningful impact in the energy sector.

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Contact Details:

ENGIE UK Recruitment Team

We think you need these skills to ace Meter Data Specialist - Hybrid Role in Energy Market Ops in Leeds

Problem-Solving Skills
Communication Skills
Attention to Detail
Python
SQL
Data Engineering
Data Pipeline Development