Data Engineer

This is a hands-on role focused primarily on building a greenfield end-to-end analytics platform, with real ownership and scope to shape how data is engineered, deployed and scaled across the organisation.

You’ll work closely with the technical lead and have the opportunity to deepen your platform and AI exposure over time — but the core focus is strong data engineering fundamentals.

The Role

You’ll design and build scalable data pipelines and backend services that power analytics, internal tools and client-facing digital products. This is a practical, delivery-focused position for someone who enjoys writing clean Python, solving data problems, and shipping production systems in the cloud.

Key Responsibilities

• Design and build data pipelines using Python and SQL
• Work with cloud infrastructure (Azure preferred; AWS/GCP welcome)
• Deploy and manage containerised services using Docker
• Embed data quality, validation and reliability best practices
• Collaborate on architectural improvements as the platform evolves
• Contribute to documentation and engineering standards
• Strong Python (production-level, OOP)
• Solid SQL and relational database experience (PostgreSQL preferred)
• Experience building ETL/ELT or data pipelines
• Comfortable working independently in a collaborative team

Desirable / Growth Areas (Not Required Day One)

• Kubernetes or broader container orchestration
• Infrastructure as Code (Terraform/Bicep/CloudFormation)
• Observability and monitoring tooling
• Exposure to analytics platforms or streaming architectures
• Interest in ML/MLOps or applied AI systems
• Experience in financial services or regulated environments

Why Apply?

• Greenfield analytics platform build
• Real ownership and technical impact
• Exposure to modern cloud and AI tooling
• Hybrid working in the City of London
• Clear opportunity to broaden into platform and AI over time

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