Head of Data Engineering

Overview

HEAD OF DATA ENGINEERING - HYBRID - LONDON

THE COMPANY This high-growth, product-led scale-up is redefining how data powers decision-making in the mobility and financial services space. By processing vast streams of behavioural and location data, the business delivers real-time insights that shape pricing, onboarding, and risk models. As they scale their data capabilities, this role will directly shape the architecture, tools, and team that underpin their most critical data products.

THE ROLE

As Head of Data Engineering, you will lead the strategic direction, architecture, and delivery of a modern, scalable data platform. You’ll oversee the ingestion, transformation, and processing of large-scale datasets, enabling high-performance analytics, real-time insights, and advanced ML use cases. This is a hands-on leadership role where you’ll grow and mentor a talented team, modernise tooling, and define best practices across the engineering organisation.

Specifically, you can expect to be involved in the following:

• Leading and mentoring a team of Data Engineers
• Designing and evolving a scalable, reliable data platform using AWS, Snowflake, Apache Spark, Airflow, dbt, Python, and SQL
• Overseeing ingestion of high-volume signal data and integrating external data sources
• Driving adoption of modern engineering practices-CI/CD, testing, infrastructure-as-code, and data governance
• Partnering with other data leaders to deliver business-aligned solutions
• Leading technical initiatives such as re-architecting pipelines, implementing real-time processing, and modernising platform tooling

SKILLS AND EXPERIENCE

The successful Head of Data Engineering will have the following skills and experience:

• 5+ years as a Data Engineer and 2+ years in a technical leadership or management role
• Proven experience designing scalable data architectures and building robust pipelines
• Strong knowledge of AWS, Snowflake, orchestration (Airflow), transformation (dbt), and large-scale processing (Spark or equivalent)
• Proficiency in Python and SQL
• Track record of delivering in fast-paced, product-led environments (start-up/scale-up experience preferred)
• Strong leadership skills with the ability to grow and inspire high-performing teams

BENEFITS

The successful Head of Data Engineering will receive the following benefits:

• Annual bonus
• Share options in a high-growth business
• Hybrid working: 1 day per week onsite in central London (Bank/Monument)
• Private health and life cover
• Generous holiday allowance and pension scheme
• Opportunity to shape the data strategy and platform of a scaling, data-led business

HOW TO APPLY

Please register your interest by sending your resume/CV to Joana Alves via the Apply link on this page.

The successful Head of Data Engineering will have the following skills and experience:

• 5+ years as a Data Engineer and 2+ years in a technical leadership or management role
• Proven experience designing scalable data architectures and building robust pipelines
• Strong knowledge of AWS, Snowflake, orchestration (Airflow), transformation (dbt), and large-scale processing (Spark or equivalent)
• Proficiency in Python and SQL
• Track record of delivering in fast-paced, product-led environments (start-up/scale-up experience preferred)
• Strong leadership skills with the ability to grow and inspire high-performing teams

The successful Head of Data Engineering will receive the following benefits:

• Annual bonus
• Share options in a high-growth business
• Hybrid working: 1 day per week onsite in central London (Bank/Monument)
• Private health and life cover
• Generous holiday allowance and pension scheme
• Opportunity to shape the data strategy and platform of a scaling, data-led business

This high-growth, product-led scale-up is redefining how data powers decision-making in the mobility and financial services space. By processing vast streams of behavioural and location data, the business delivers real-time insights that shape pricing, onboarding, and risk models. As they scale their data capabilities, this role will directly shape the architecture, tools, and team that underpin their most critical data products.