Analytics Engineer (UK Cards)

About This Opportunity

We are representing a confidential fintech organization in their search for an Analytics Engineer to join their UK Cards team. This is a chance to work on the analytical foundation of a fast-growing product area, building data models that support critical business decisions.

You'll collaborate with analysts, product teams, and engineers to transform how data is structured and consumed. The role centers on creating reliable, scalable pipelines that help teams move from questions to insights quickly while maintaining high data quality standards.

Responsibilities

• Build and refine data models supporting lending decisions, pricing analysis, portfolio reporting, and investor communications
• Champion analytics engineering standards and contribute to evolving the team's data culture
• Collaborate with analysts across technical skill levels, translating requirements into robust data pipelines
• Triage and resolve pipeline issues that affect data trust or downstream consumption
• Identify opportunities to improve efficiency, reliability, and cost-effectiveness of transformation workflows
• Work within a modern stack including SQL, Snowflake, dbt, Fivetran, and AI tools

What We're Looking For

• Strong data modelling fundamentals with practical application in fast-paced environments
• Solid experience designing analytical datasets for reliability and usability
• Proven track record with ELT pipelines and transformation at scale, ideally using dbt
• Experience with Snowflake or similar modern cloud data warehouses
• Proactive mindset in identifying workflow improvements and proposing solutions
• Clear communication skills across both technical and non-technical stakeholders
• Comfort leveraging AI tools to accelerate work quality and efficiency
• Collaborative working style and ability to explain technical tradeoffs to varied audiences

How We Work With You

Candidates apply through Get A Job.ai. Our talent team conducts an initial screening to understand your background and fit. We then coordinate your interview process with our client, which includes:

• Initial call with an engineer
• 15-minute cognitive assessment
• 90-minute onsite or video interview (team introduction, architecture exercise, Q&A)
• 60-minute stakeholder discussion covering cultural fit, product thinking, and collaboration style

Please do not contact the employer directly—all communication goes through our recruiting team to ensure a smooth process.

Pay

Compensation details will be discussed during the screening process based on experience level and market benchmarks.

Equal Opportunity

Get A Job.ai is committed to inclusive hiring practices. We welcome applications from all qualified candidates regardless of race, color, religion, sex, national origin, age, disability, or veteran status.