Lead Analytics Engineer

Allica Bank; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Onboarding support

Flexible working

Social activities

Pension contributions

Discretionary bonus scheme

Private health cover

Life assurance

Family friendly policies

Job summary

Allica Bank is seeking a Lead Analytics Engineer to own the Lending data product on GCP and Looker. You will bridge analytics, data engineering and business stakeholders to deliver scalable, well-governed data models that support reporting, decision-making and emerging GenAI use cases.

The role combines hands-on delivery with leadership of an analytics engineering squad, setting standards for data modelling, validation, and usage across the Lending domain, and guiding data quality and governance

Qualifications

• Strong SQL and data modelling experience in BigQuery or similar data platforms.
• Experience working with BI semantic layers (Looker preferred).
• Solid understanding of lending/financial services data flows and governance.

Responsibilities

• Own and evolve the Lending data model across BigQuery and Looker.
• Lead data modelling, validation and usage standards for the Lending domain.
• Drive data quality and governance across datasets and data products.

Skills

SQL

Data modelling

Tools

BigQuery

Looker

Job description

About Allica Bank

Allica is the UK's fastest growing company - and the fastest-growing financial technology (Fintech) firm ever. Our purpose is to help established SMEs, one of the last major underserved opportunities in Fintech.

Established SMEs are the backbone of local communities - representing over a third of our economy - yet have been largely neglected both by traditional high street banks and modern fintech providers.

Role Description

The Lead Analytics Engineer owns the design, delivery, and ongoing evolution of the Lending data product on GCP and Looker. This role bridges analytics, data engineering, and business stakeholders to deliver scalable, well-governed data models that support reporting, decision-making, and emerging AI-driven use cases.

The role combines hands-on technical delivery, with leadership of an analytics engineering squad, setting standards for data modelling, validation, and usage across the Lending domain.

Principal Accountabilities

Data Product Ownership

• Own and evolve the Lending data model across BigQuery and Looker


• Deliver standardised, scalable data models (gold + semantic layers)


• Ensure data models accurately reflect lending business logic and requirements


• Drive data quality, validation, and consistency across datasets

Technical Leadership

• Define and implement best practices for analytics engineering (modelling, naming, documentation, testing)


• Lead design and code reviews across the analytics engineering workstream


• Act as the subject matter expert on Lending data structures and behaviour

Delivery & Workstream Leadership

• Lead the GCP and Looker data workstream, including sprint planning and prioritisation


• Translate business requirements into structured engineering tasks and delivery plans


• Ensure high-quality and timely delivery of data assets

Stakeholder Engagement

• Partner with Lending, Risk, Product, and Engineering teams to define data requirements


• Translate business metrics into structured data models and definitions


• Provide clarity and guidance on data usage across the organisation

Team Leadership & Development

• Provide technical mentorship to analysts and engineers within the Lending squad


• Support workload allocation and delivery across the squadlet structure


• Contribute to building strong, collaborative ways of working

Strategic Contribution

• Lead development of the unified Lending data model, a key strategic initiative


• Contribute to building data context (metadata, definitions, relationships) to enable self-serve analytics and GenAI use cases


• Support the organisation’s transition to GCP and Looker platforms

Personal Attributes & Experience

Technical

• Strong SQL and data modelling experience (BigQuery or similar preferred)


• Experience working with BI semantic layers (Looker preferred)


• Proven ability to design and deliver scalable data models

Domain & Problem Solving

• Strong understanding of data flows across complex systems (particularly lending or financial services)


• Ability to translate business requirements into technical solutions


• Structured, engineering-led approach to problem solving

Leadership

• Experience leading technical workstreams or projects


• Ability to mentor and develop team members


• Strong ownership mindset and ability to operate independently

Scope & Impact

• Owns the Lending data product (GCP + Looker)


• Leads analytics engineering delivery for Lending


• Plays a critical role in enabling reporting, risk management, and strategic analytics across the bank


• #LI-AD1

Working at Allica Bank

At Allica Bank we want to ensure our employees have the right tools and environment in which to succeed in their role and in support of our customers.

Our employees are at the heart of everything we do, so our benefits are designed with you in mind:

• Full onboarding support and continued development opportunities


• Options for flexible working


• Regular social activities


• Pension contributions


• Discretionary bonus scheme


• Private health cover


• Life assurance


• Family friendly policies including enhanced Maternity & Paternity leave

Don’t tick every box?

Don’t worry if you don’t have all the skills or requirements listed on the job description. If you think you’ll be a good fit, we’d still love to hear from you!

Flexible working

We know the '9-to-5' isn’t right for everyone. That’s why Allica Bank is fully committed to flexible and hybrid working. Please let us know what is best for you and, if we can, we will do our best to accommodate.

Diversity

We're a diverse bunch here at Allica, with all kinds of experiences, backgrounds and lifestyles. Our openness and differences make us stronger, and we want everybody to feel comfortable bringing as much of themselves to work with them as they like.