Head Of Data Engineering & Infrastructure

Location: London Office / Hybrid (3 days a week working from home)

Reporting to: Director - Data & Analytics

The Role : Head of Data Engineering & Infrastructure

This role offers a unique opportunity to lead and shape the data engineering strategy at an organisation that values the transformative power of data. As Head of Data Engineering and Infrastructure, you will drive the development of scalable and resilient data infrastructure, enabling the business to unlock insights and foster innovation. You will work at the intersection of advanced analytics, cloud technologies, and data science, playing a pivotal role in accelerating AI and delivering a unified data platform.

You will lead a high-performing team of data engineers, collaborating closely with cross-functional departments to drive business growth and enhance the customer and partner experience. The ideal candidate will bring a mix of technical expertise, leadership skills, and strategic thinking to champion data-driven initiatives that align with organisational goals.

Key Responsibilities:

• Define and implement a data engineering strategy aligned with the organisation's objectives and technological advancements, ensuring scalability and adaptability.
• Lead the design and delivery of a modern cloud data platform, optimising for scalability, reliability, and cost-efficiency.
• Integrate emerging technologies, such as AI and real-time analytics, into the data infrastructure to enable advanced data processing capabilities.
• Promote a data-driven culture by implementing best practices, shaping data governance frameworks, and fostering innovation in data processes.
• Partner with senior leadership to ensure alignment between data engineering initiatives and business strategy, driving value through data-driven decision-making.
• Optimise data workflows and algorithms to improve performance and reduce latency while maintaining resource efficiency.
• Ensure the integrity and accuracy of data assets through robust quality assurance processes.
• Lead and mentor a team of data engineers and database architects, encouraging continuous learning and professional development.
• Foster collaboration with cross-functional teams to drive interdisciplinary innovation and problem-solving.
• Represent data engineering in senior stakeholder meetings and external industry events, advocating for data as a strategic asset.
• Build relationships with external partners and vendors to stay informed about the latest trends and technologies in data engineering.

What We're Looking For:

• A strategic mindset with the ability to translate goals into actionable plans and deliver organisational change.
• Proven leadership skills to inspire and support a high-performing data engineering team, building trust and fostering a culture of growth and belonging.
• Expertise in end-to-end data science infrastructure development to enable AI and advanced analytics.
• Strong analytical and business acumen to create impactful data and cloud solutions.
• Exceptional communication and collaboration skills, with the ability to convey complex technical concepts to diverse audiences.
• Proficiency in programming languages (e.g., Python, Scala, SQL) and cloud platforms (GCP, AWS, Azure), with a strong grasp of data processing and analytics services.
• Results-oriented with a focus on delivering measurable outcomes, setting clear goals, and tracking progress through OKRs and KPIs.
• Passion for innovation and a proactive approach to exploring new technologies and best practices.
• Adaptable and resilient, thriving in dynamic and fast-paced environments.

Preferred Qualifications and Experience:

• A Bachelor's or Master's degree in Engineering, Computer Science, Mathematics, or a related STEM field, or equivalent data engineering experience.
• Deep understanding of data engineering methodologies, including data modelling, ETL/ELT processes, data mesh, and distributed computing.
• Experience with big data technologies like Spark and Kafka, and database systems with a focus on performance optimisation.
• A proven track record of building and leading successful data engineering teams and delivering impactful projects.
• Demonstrated ability to balance technical feasibility with business impact and ROI in decision-making and project prioritisation.