Head of Data Platform, Feefo

• Bachelor’s degree in Computer Science, similar technical discipline or demonstrable equivalent career experience
• At least six years of commercial data engineering or data architecture experience
• Experience of developing solutions within public cloud, preferably Google Cloud Platform
• Proven experience in architecting complex software solutions and researching the appropriate technologies to deliver them
• Experience of greenfield Data Warehouse implementations, including Data Architecture principles
• Appreciation of data science concepts and ability to promote solutions to production via machine learning engineering
• Expert hands-on knowledge of NoSQL and relational Databases, alongside relevant data modelling techniques
• Experience of Fivetran or similar ETL/ELT tooling
• Experience defining and implementing Data Governance at scale within a lakehouse architecture
• Working knowledge of DBT, Luigi or similar orchestration tooling
• Experience of managing and developing a team in an agile environment
• Experience of Agile development design principles
• Experience of managing and working with co-located and remote developers
• Source version control, ideally GitHub
• Development using industry standard best practices
• Test driven development or business driven development experience
• Working knowledge of Continuous Integration solutions and best practice branching strategies
• Outstanding oral and written communication skills, capable of achieving consensus across both technical and non-technical audiences
• Experience of machine learning engineering tools on GCP

Desirable

• Reporting to our CTO the Head of Data Platform acts as one of three department heads leading the Technology Team’s data engineering and data science experts
• You will have a specific focus across the wider team on the advocacy of data engineering excellence backed by your domain expertise and passion for data technologies
• Beyond your technical contributions your key priority as a leader of people is to build and maintain a high calibre team, safeguard their health, and enable them to succeed in delivering high performance and productivity
• To design, build & maintain a scalable, efficient and secure data platform which provides a solid foundation for Feefo to deliver clients with unrivalled actionable insight
• Creatively sequence near term tactical solutions which unlock rapid value to clients in parallel with longer term strategic architecture plans
• Define and execute a scalable AI strategy which drives innovation, efficiency and value, taking into consideration key aspects such as risk, ethics, compliance and governance
• Evolve, contribute and deliver against the Technology Team’s strategy and quarterly OKRs
• Work closely with our product team to understand the problems we need to solve for our clients and how these can be met with creative technical solutions
• Inspire best practice for data products and services across the organisation
• Build our data engineering capability by providing technical leadership and career development for the department and wider data community
• Continually strive to build and maintain a high-performance culture within your team
• Create opportunities for engineers to grow their skills and experience
• Hold regular 1:2:1s with members of your team, giving frequent actionable feedback on their performance
• Continuous improvement/evolution of our agile engineering practices
• Fostering autonomy and self-organisation within our engineering pods, making final decisions when necessary
• Monitor and safeguard the psychological safety of your team
• Encourage alignment across the team on standards of practice and design patterns
• Establish effective mechanisms for distributing knowledge, working against single points of failure
• Responsible for the data platform spanning:
• Data Quality - ensuring source systems are running well and to best engineering practices and data from these systems is ingested correctly and completely
• Data Governance - Maintaining the business data twin definitions and quality, providing improvements and expanding the definitions, when necessary
• Efficient Infrastructure - Ensuring the infrastructure is well maintained, tools are available and kept up to date
• Product-ionisation - Data related workflows and pipelines are organised within the company’s best practice guidelines and agreed formats and orchestration are running correctly and on time without operational overhead
• Data Access Management - Implementation of access controls and permissions to ensure data security and compliance with regulatory requirements
• Model Development - Creating effective and efficient ML and analytical models that are trained ethically and produce unbiased results
• Data Security and Compliance - Adherence to data privacy regulations and implementation of security measures to protect client data
• Contribute towards programme level planning from both an execution and architectural perspective
• Investigate emerging trends in data-related approaches, perform horizon-scanning for the organisation and introduce innovative ways of working