Lead Data Engineer

Location: London

Reporting To: Chief Technology Officer

About Us

Our client is a leading AI-powered SaaS company that helps businesses unlock the full potential of their first-party data. Their platform transforms complex data into actionable intelligence, enabling clients to drive revenue growth and optimise decision-making. They specialise in Finance, Retail, Travel, Telco, and Healthcare, working with major household-name brands. Currently serving clients in four countries with two live products and two AI solutions in development, this is an exciting time to join as they scale rapidly.

Role Overview

This is a player-manager role leading the Data Engineering function. You'll define processes, tooling, quality standards, and team structure while personally delivering on the most complex pipeline work. You'll manage and mentor data engineers, own the data infrastructure, and collaborate across Product, Data Science, Client Success, and Platform R&D. You'll also lead the adoption of AI within the engineering workflow.

Key Responsibilities

Function Leadership & Team Management

• Own the Data Engineering function: standards, tooling, and delivery processes
• Manage, mentor, and develop a team of data engineers including performance and development plans
• Lead recruitment and be the engineering voice in cross-functional planning

Data Engineering & Architecture

• Design and build high-performance ETL/ELT pipelines across operational, analytical, and AI data layers
• Lead schema design, model validation, scalable partitioning, and metadata-driven SQL frameworks
• Hands-on ownership of the most complex implementation work

Data Modelling & Design

• Define and evolve data models powering SCV, segmentation, AI features, and analytics
• Work across dimensional, event-based, and ML-aligned data structures

DevOps, CI/CD & AI Ops

• Own CI/CD for data pipelines using Git-based workflows, deployment governance, and rollback handling
• Orchestrate ML model outputs into production pipelines with resilience controls
• Drive AI tooling adoption across engineering: code generation, data profiling, documentation, and testing
• Implement structured logging, alerting, SLA tracking, and access control

Key Technologies

• Cloud: Azure, AWS, or GCP | SQL (T-SQL, PostgreSQL), Python, versioned metadata frameworks
• DevOps: Git, CI/CD (Azure DevOps, GitHub Actions) | Monitoring: Custom logging, alerts, structured failure handling
• Security: Role-based schema access, PII isolation, audit trails

Required Skills & Experience

• First-class STEM degree from a prestigious university
• 5+ years in Data Engineering/Platform roles, 2+ years in a lead or senior capacity
• Proven line management experience — not just technical leadership
• Track record of building or improving engineering processes and team structures
• Expertise in SQL pipelines, Python orchestration, dimensional modelling, and star/snowflake schemas
• Experience with cloud data infrastructure, CI/CD automation, and metadata frameworks
• Comfortable working across product, AI, and client delivery teams

Why Join?

• Build and lead a Data Engineering function from the ground up
• Work on real-world AI challenges for enterprise clients across multiple sectors
• Direct mentorship from the CTO and Technical Architect
• Competitive salary, learning budget, and fast-track growth