Data Engineering Lead

Lloyds Banking Group
Leeds
2 weeks ago
Create job alert

WORKING PATTERN: Hybrid, minimum 40% in the office


About the Role

You’ll join as the new Data Team Engineering Lead within IP&I Colleague & Customer Service Platform (CCS). You will empower, mentor, and support the engineering group passionate about data. They work in cross-disciplinary teams delivering customer focused solutions and high-quality software.


Collaborate with the Lab Product Owners, Lead Integrators, Customer Journey Managers, Product Managers and Data Analytics and Strategy Managers to facilitate and resolve the Lab’s data requirements.


Showcasing your excellent interpersonal and communication skill whilst efficiently working across the project life cycle. You’ll represent Engineering and speak for the engineering groups. You will help identify and support teams in overcoming impediments and issues. You will also keep developing your skills with the processes and tools used by the data engineering team.


This is a leadership level role and will blend both deep domain and technical expertise within a feature team and phenomenal passion for coaching and developing people in a “player-coach” model.


About us

Like the modern Britain we serve, we’re evolving. Investing billions in our people, data and tech to transform the way we meet the ever-changing needs of our 26 million customers. We’re growing with purpose. Join us on our journey and you will too…


What You’ll Need
Technical Leadership

  • Define and implement the engineering strategy for data solutions within IP&I CCS.
  • Ensure alignment with enterprise architecture standards and regulatory requirements.
  • Build, develop and maintain sophisticated Data Products, implementing clean, maintainable and efficient solution composition following established guidelines.

Delivery Excellence

  • Own the build and development of reliable data workflows and integration solutions.
  • Excellent problem solving abilities alongside keen reasoning to resolve complex data issues, technical problems and bugs.
  • Oversee Data Producer and Consumer responsibilities, ensuring minimal disruption to business operations.
  • Ensure timely delivery by managing tasks and priorities effectively utilising their in-depth expertise in Agile methodology.

Team Development

  • Mentor and coach engineers within the team, fostering a culture of teamwork and continuous improvements.
  • Support career development and technical upskilling in cloud technologies and modern data practices.

Stakeholder Engagement

  • Work closely with Product Owners, customer experience coordinators, and Proposition Managers to prioritize and deliver data capabilities that meet business needs.
  • Communicate technical concepts clearly to non‑technical stakeholders.

Governance & Compliance

  • Ensure adherence to data governance, security and compliance standards relevant to financial services.
  • Accountable for custodianship governance activities on data assets that their platform produces and consumes,
  • Embed quality assurance and testing practices across all deliverables.
  • Review and lead the cloud costs of the Lab and the platform.
  • Champion the adoption of modern engineering practices (CI/CD, DevOps).
  • Identify opportunities to optimise data pipelines and introduce automation.

Core Skills & Experience

  • Experience leading data engineering teams in complex, regulated environments.
  • Understanding of the Business Context, Data Migration strategies and integration patterns.
  • Hands on experience in designing, building and maintaining robust data pipelines.
  • Experience in Python for Data Transformation and Google Big Query.
  • Working knowledge across Data Modelling and Visualisation Tools like Power BI, Tableau.
  • Expertise in ETL and Cloud Technologies (GCP Preferred).
  • Familiarity with Data Governance Framework.
  • Excellent leadership, communication and stakeholder management skills.
  • Strong problem‑solving and analytical skills.

Our focus is to ensure we’re inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity or culture.


We were one of the first major organisations to set goals on diversity in senior roles, create a menopause health package, and a dedicated Working with Cancer initiative.


And it’s why we especially welcome applications from under‑represented groups.


We’re disability confident. So if you’d like reasonable adjustments to be made to our recruitment processes, just let us know.


Benefits

  • A generous pension contribution of up to 15%
  • An annual bonus award, subject to Group performance
  • Share schemes including free shares
  • Benefits you can adapt to your lifestyle, such as discounted shopping
  • 30 days’ holiday, with bank holidays on top
  • A range of wellbeing initiatives and generous parental leave policies

Want to do amazing work, that's interesting and makes a difference to millions of people? Join our journey.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineering Lead

Data Engineering Lead

Data Engineering Lead- Manchester (hybrid) - up to £80K DOE

Data Engineering Lead

Data Engineering Lead — Hybrid, Drive Data Delivery

Data Engineering Lead: Fabric/Azure DWH & ETL

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.