Job Description

End Date

Thursday 22 October 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

Lead Data Engineer – Grade F

Why Lloyds Banking Group

We're on an exciting transformation journey and there could not be a better time to join us. The investments we're making in our people, data, and technology are leading to innovative projects, fresh possibilities and countless new ways for our people to work, learn, and thrive.

About this Opportunity

Join one of Lloyds Banking Group's most ambitious Relationship Manager Transformation programmes, building the data and AI foundation that will redefine how colleagues serve customers across Commercial Banking.

This role sits at the heart of a multi-year transformation, creating trusted data products, real-time insights, and AI-ready platforms that power the next generation of CRM, servicing, and relationship management.

Location: Hyd

YOE: 17-22

Mode: Hybrid

Job Description

Key Activities / Responsibilities

In this role, you'll play a pivotal role in crafting and implementing data solutions on Google Cloud Platform (GCP) leading and collaborating with multi-functional teams to ensure seamless integration of data products into our new data architecture, driving innovation and optimising data utilisation.

Your role would include the following activities:

• Design, develop, and maintain complex Data Products. Implementing clean, maintainable, and efficient solution design following best practices.
• Lead implementation reviews and all aspects of data product delivery to preserve quality and share knowledge.
• Be responsible for leading a talented group of engineers, guiding and working alongside them on entire software development lifecycle and manage the delivery of robust, scalable data applications and features.
• Evaluate and recommend tools, technologies, and processes to ensure the highest quality product platform.
• Identify and implement best practices for data engineering.
• Excellent problem solving and analytical skills to resolve complex data issues, technical problems, and bugs.
• Provide guidance and mentorship to engineers.
• Strong understanding of data security principles and secure architectural practices
• Knowledge of DevOps practices and CI/CD pipelines
• Ensure timely delivery by managing tasks and priorities effectively utilising their in-depth expertise in Agile methodology.
• Communicate effectively with team and stakeholders.
• Accountable for custodianship governance activities on data assets that their platform produce and consume.

Recruitment Priority Skills

We're keen to speak to candidates with experience who have strong skills in :

• Data Engineering: Can develop data validation methodology and data hub process models, including sourcing, loading, transformation and extraction in alignment with the Group and business needs.
• Data Modelling & Design : Can aligns models to domain boundaries and real access patterns across services, streams, and warehouses. Designs for evolvability using additive changes, backward‑compatible schemas, and safe deprecations. Can embed data quality checks, defines conformed dimensions and a semantic layer, and implements privacy and security controls such as row/column‑level security and PII handling. Experience of coaching others and enforcing standards through reviews and reusable templates.
• Dev Ops: Leading team to identify issues and improve automation across the end-to-end application development lifecycle. Using technology stack and tooling to evolve applications at pace and ensure efficiency, quality and security is monitored as part of every build.
• Python: Has a holistic understanding of Python and can make intuitive decisions in familiar contexts. Capable of implementing multi-threading and asynchronous programming using tools like threading and asyncio.
• SQL: Can tune complex queries and workloads; designs schemas and constraints; manages concurrency/isolation; refactors for performance and readability; mentors others
• Leadership & People Development: Builds, inspires, and scales high-performing Data Engineering, Analytics, and Modelling teams. Creates a culture of ownership, innovation, and continuous improvement through effective coaching, mentoring, talent development, and servant leadership.

Other Key Skills

Technical Skills

· AI Literacy

· Data Architecture

· Quality Engineering

· Agile Methodology & Tools

· Expertise in FinOps/Optimisation for Cloud Computing

· Google Analytical Database technologies (Big Query, Cloud SQL, Spanner, AlloyDB)

· Infrastructure as Code experience

· Streaming platforms knowledge and utilisation (Pub/Sub or Kafka for example, Dataflow, Flink for example)

· Build/Deploy container-based solutions (GKE)

· Building solutions to provide Data Quality (Dataplex, Atacama etc)

· Exposure and experience to modern programming practices (Functional programming, Event-based solutions)

Personal:

· Communication

· Customer centricity

· Critical thinking

· Data Literacy

· Data Storytelling