Data Engineer

Job Description

Data Engineer (Fintech) — Data & AI team

We’re hiring an experienced Data Engineer to join a high-performing Data & AI team within a fast-scaling fintech. This is a hands-on role building modern data products end-to-end, using AI to accelerate delivery while maintaining strong engineering standards around governance, quality and scalability.

Over the last 12 months the team has attracted exceptional engineering talent, creating an environment where you’ll learn quickly and ship meaningful work. AI is actively integrated across the organisation, and you’ll help take those use cases further building reliable foundations and turning them into production ready capabilities.

You’ll contribute to high-impact workstreams including investor-style onboarding flows, entity and account structures, and a portfolio performance monitoring product that delivers monthly updates on how assets and exposures are progressing, and then rotate across domains over time to broaden your technical depth and product understanding.

What you’ll do

• Build and scale data pipelines and data products using Python and SQL
• Use AI-enabled approaches to deliver high-quality data solutions faster, without compromising best practice
• Own delivery within your domain: data quality, documentation, accountability and maintainability
• Translate business needs into clear technical requirements and robust data models
• Build API-based integrations with source systems and deliver analytics-ready datasets
• Help improve how the team ships: testing, CI/CD patterns, orchestration and continuous improvement

What we’re looking for

• Strong Python and SQL (comfortable coding from scratch)
• Influence on business operations (stakeholders) and API based integrations
• Experience building reliable ETL/ELT pipelines and production data models
• Strong data modelling fundamentals and ability to communicate with stakeholders
• Exposure to AI-enabled workflows is a plus (e.g., using AI tools to accelerate engineering, or supporting AI use cases with trusted data)
• DBT experience is a big plus
• Snowflake experience is helpful (not essential)
• 2+ years’ experience in data engineering or related fields (level flexible based on impact)