At a Glance
- Tasks: Lead the design and delivery of innovative Lending data products using GCP and Looker.
- Company: Join Allica Bank, the UK's fastest-growing fintech, dedicated to supporting SMEs.
- Benefits: Enjoy flexible working, private health cover, and a supportive development environment.
- Other info: Be part of a diverse team with excellent career growth opportunities.
- Why this job: Make a real impact in fintech by enhancing data-driven decision-making for local businesses.
- Qualifications: Strong SQL skills and experience in data modelling; leadership experience is a plus.
The predicted salary is between 49500 - 60500 £ per year.
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 Big Query 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 Gen AI use cases
- Support the organisation’s transition to GCP and Looker platforms
- Personal Attributes & Experience
- Technical
- Strong SQL and data modelling experience (Big Query 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.
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Lead Analytics Engineer employer: Allica
Allica Bank is an excellent employer that prioritises employee growth and development within a dynamic and supportive work culture. Located in a vibrant area, we offer competitive benefits and the opportunity to make a meaningful impact in the lending sector, ensuring fair outcomes for our customers while fostering strong relationships. Join us to be part of a team that values innovation and collaboration as we scale our operations.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Analytics Engineer
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Analytics Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Allica. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Allica
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Allica!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
