Lead Engineer (EDP) – Data Transformation & Modelling Lab at Lloyds Banking Group
Manchester, England, United Kingdom -
Full Time


Start Date

Immediate

Expiry Date

27 Nov, 25

Salary

90440.0

Posted On

28 Aug, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Good communication skills

Industry

Information Technology/IT

Description

JOB DESCRIPTION

JOB TITLE: Lead Engineer (EDP) – Data Transformation & Modelling Lab
SALARY: £90,440 – £106,400 (Manchester) | £104,686 – £123,160 (London)
LOCATION(S): Manchester or London
HOURS: Full-time – 35 hours per week
WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time, at our Manchester or London office.

Responsibilities

You’ll be joining the Data Transformation & Modelling Lab, a key part of our Data & Machine Learning Platform. The Lab plays a central role in shaping the bank ’ s future data landscape by:

  • Designing and maintaining the Group Data Model, ensuring consistency, reusability, and alignment with enterprise-wide data standards.
  • Building high-quality data products that serve as trusted, reusable assets across the organisation.
  • Developing toolkits and accelerators to enable rapid, secure, and scalable data migration to Google Cloud Platform ( BigQuery ).
  • Underpinning our strategy for Generative AI and Agentic AI, by ensuring data is well-modelled, governed, and accessible for advanced analytics and AI use cases.
  • We work in agile, cross-functional teams following Scrum principles — focused on iterative delivery, continuous improvement, and close collaboration with stakeholders.
  • As a Lead Engineer, you ’ ll help define technical direction, mentor engineers, and deliver the foundational data capabilities that power the bank ’ s digital and AI-driven future

What you’ll do

  • Designing and evolving conceptual, logical, and physical data models aligned to business domains and data mesh principles.
  • Collaborating with domain teams to define and deliver high-quality, reusable data products on BigQuery .
  • Leading the transformation of legacy data models from on-premise platforms to cloud-native equivalents.
  • Ensuring data models are optimised for performance, scalability, and cost-efficiency in BigQuery .
  • Supporting the development of modelling standards, patterns, and best practices across the engineering community.
  • Partnering with data architects, engineers, and product owners to align modelling with enterprise architecture and strategic goals.
  • Mentoring junior engineers and modellers, fostering a culture of continuous learning and technical excellence
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