Head of Data Engineering

Location:Hybrid, London

Salary:Up to £120,000 (Maybe £130,000) + 10% Bonus

Overview:

We are seeking an experienced and innovative Head of Data Engineering to lead the development of a cutting-edge Data Platform within a fast-growing Insurtech company. As a key figure in the Data team, you’ll drive the strategic direction of both the Data and AI/ML platforms, playing a pivotal role in providing high-quality insights to insurer and broker customers. This is an exciting opportunity to build and scale a Data Engineering function from the ground up, leading a talented team while shaping the future of data within the business.

Key Responsibilities:

• Lead, mentor, and grow a high-performing team of Data Engineers and Machine Learning Engineers, fostering a collaborative and innovative culture.
• Design, implement, and maintain a scalable, automated, and industry-leading Data Platform.
• Develop and execute the roadmap for a greenfield AI/ML platform, ensuring alignment with business goals.
• Collaborate closely with data analysts, data scientists, and the wider engineering team to deliver impactful data and analytics products.
• Work with the engineering function to manage cloud resources, leveraging infrastructure-as-code tools.
• Establish a robust FinOps strategy, optimizing costs across the data platform.
• Ensure compliance with data access, privacy, and security standards.
• Stay informed on emerging technologies, providing thought leadership on the future of data practices within the company.

Ideal Candidate Profile:

• Proven experience in building and growing high-performing Data Engineering teams.
• Strong track record of delivering data science products with significant commercial impact.
• Deep expertise in developing Data Platforms and AI/ML platforms within a public cloud environment.
• Hands-on experience with ETL/ELT tools such as Azure Data Factory, Fivetran, Matillion, or DBT.
• Proficiency in scripting and automation (Python, Terraform, or similar).
• Expertise in SQL (Postgres or similar), with knowledge of NoSQL technologies (e.g., MongoDB).
• Familiarity with orchestration tools (Airflow, Argo, or similar).
• Experience implementing CI/CD practices and monitoring for data/ML pipelines.