VP Engineering - Data Products

About this role

Job Description: We are looking for a senior engineering leader to own the technical roadmap for our enterprise-scale data and AI infrastructure. You will lead a multi-disciplinary engineering organization, set data platform and cloud architecture direction, and act as the bridge between hands-on solution design and commercial/vendor accountability. This role combines strong architectural credibility with people leadership, governance ownership, and stakeholder management across global clients.

Responsibilities • Lead, grow and develop a multi-disciplinary engineering organization, providing mentorship to Development Leads and engineers, ensuring team composition is adequate, and hiring to fill gaps.

• Set and own the technical roadmap for the data platform, defining reference architectures and design patterns (e.g. medallion/layered architectures) that scale across multiple business units and data domains.

• Provide guidance, coaching and mentorship in modern data engineering practices, web application development, and best practices for diagnostics, debugging, testing, deploying, and troubleshooting.

• Work with Product and Engineering teams to scope, plan and estimate the technical roadmap, aligning it to broader business goals and helping to forecast delivery timescales.

• Evaluate solution options against business requirements and organizational standards; champion rapid prototyping and proof-of-concept work to validate designs and de-risk delivery.

• Provide architectural oversight and mentorship to architects and engineers; maintain high standards of design documentation and contribute to the evolution of architectural reference models.

• Foster constructive debates between Product, Engineering and UX teams to create scalable, client-focused solutions that solve business problems with software in the shortest sustainable lead-time.

• Establish and run governance frameworks for applications and data products, including certification and stewardship processes; ensure compliance with security, data privacy, and regulatory standards.

• Own platform security posture: access control, secrets management, naming/tagging conventions, and certification of new data products. Lead the triage and remediation of platform security or data incidents.

• Build visibility into cloud and compute cost drivers; drive FinOps practices to optimize spend across environments. Design repeatable onboarding processes for new tools, analysts, and integrations.

• Manage vendor relationships, procurement processes and commercial contract negotiations, ensuring legal and compliance requirements are met. Provide technical oversight of 3rd party supplier partnerships.

• Lead platform modernization and migration programs, including planning, sequencing, and risk management for large-scale technology transitions.

• Stay up to date with emerging technologies and industry trends, assessing their potential impact and benefit to the overall business strategy, particularly AI/agentic capabilities and data infrastructure innovations.

Candidate Profile • Proven experience leading data engineering or data platform teams at a senior/head level, ideally within a large or matrixed organization.

• Industry experience working with Data platforms is essential, with strong background in dimensional data modelling, data pipeline development and data engineering in support of web applications.

• Strong hands-on background in modern cloud data platforms (e.g. Databricks, Snowflake, or equivalent) and major cloud providers (Azure, AWS, or GCP).

• Solid understanding of data governance, access control, and security practices in cloud environments.

• Experience with large-scale ETL/ELT design and migration programs.

• Demonstrated experience with cloud cost management and FinOps practices.

• Experience managing vendor contracts, procurement, and commercial negotiations.

• Strong stakeholder management skills with the ability to communicate effectively across technical and non-technical audiences and global/matrixed teams.

• A structured, specification-driven approach to requirements and delivery, with a preference for disciplined, release-oriented delivery.

• Able to demonstrate evidence of applying technology to solve business problems.

Requirements • Strong working knowledge of modern cloud data platforms (Azure Databricks/Spark using Python and associated frameworks, or Snowflake equivalent).

• Strong working knowledge of cloud storage solutions (Azure Data Lake, Blob storage, or equivalent).

• Strong experience of building data reporting and visualisations using PowerBI, Tableau, or equivalent tools.

• Strong knowledge of SQL and data modelling principles.

• Experience in application development with proficiency in Python or JavaScript frameworks.

• Strong knowledge and experience of hosting in major cloud platforms (Azure, AWS, or GCP).

• Familiarity with how AI/ML and agentic systems are integrated with enterprise data platforms.

• Solid understanding of data governance, access control, and security practices in cloud environments.

• Knowledge of delivering solutions using a microservice architecture with RESTful protocols and event-driven architectures.

• Knowledge and experience of implementing Continuous Integration and Continuous Delivery.

• Ability to quickly learn and apply emerging programming languages, frameworks, and platforms.

• Comfortable working in an agile environment.

• Excellent communication and collaboration skills with the ability to explain technical solutions clearly to both technical and business audiences.

Preferred • Experience in building applications in MERN (Mongo, Express, React, Node) using Webpack, Typescript, and GitHub.

• Experience with Docker and/or Kubernetes and containerized deployments (AKS).

• Experience with workflow orchestration tools such as Apache Airflow or n8n.

• Experience of code quality, test, CI/CD and package managers such as Jest, Lint, Bri

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