Data Platform Lead

Role Purpose

As a Data Platform Lead, you will be responsible for the design, development, and evolution of our enterprise data platform. This is a hands-on technical leadership role, where a significant portion of your time will be spent designing solutions, building platform capabilities, reviewing code, and making architectural decisions.

You will lead a team of Data Engineers, defining technical standards for data ingestion, modelling, governance, and reusable data products, while also coaching and supporting the team's growth. Working closely with Architecture, Product, and Governance stakeholders, you will help ensure the platform is scalable, secure, and built to support the company's future data and AI ambitions.

This is not a pure people-management role. We are looking for someone who enjoys being hands-on, stays close to the technology, and can combine technical leadership with active contribution to engineering delivery.

Responsibilities

• Design and build core components of our data platform, including data ingestion, modelling, and reusable data products.
• Define standards and best practices for data ingestion, transformation, and canonical/conformed data modelling.
• Drive architectural decisions and ensure alignment with data governance, privacy, and security requirements.
• Remain hands-on by writing code, reviewing pull requests, and contributing directly to platform development.
• Establish and improve practices around data quality, lineage, access control, and governance.
• Provide technical leadership, mentoring, and coaching to Data Engineers.
• Own and prioritise the technical roadmap, balancing new capabilities with maintenance and technical debt.
• Partner with business and technology stakeholders to translate requirements into scalable technical solutions.
• Support hiring, onboarding, and development of engineers within the team.
• Promote strong engineering practices, including code quality, testing, automation, and documentation.

Requirements

• Proven experience designing and building enterprise-scale data platforms, ideally using Databricks or a similar lakehouse architecture.
• Strong expertise in data ingestion, canonical/conformed data modelling, and reusable data products.
• Strong understanding of data governance, data quality, lineage, access control, security, privacy, and anonymisation in regulated environments.
• Ability to define technical direction and drive adoption of architectural standards and best practices.
• Experience mentoring engineers through coaching, code reviews, and technical guidance while remaining actively involved in delivery.
• Comfortable operating as a player-coach, balancing hands-on engineering with team leadership.
• Knowledge of data mesh and federated data product architectures.
• Experience with cloud-native data platforms and modern data engineering tooling.
• Strong communication skills, with the ability to explain technical concepts to both technical and business audiences.
• Pragmatic approach to balancing technical quality, delivery speed, and team development.
• Experience designing and exposing data products through REST and GraphQL APIs, including schema governance, versioning, and contract management.
• Strong programming skills in Python and/or Scala, SQL, and Infrastructure as Code (Terraform preferred).
• Familiarity with knowledge graph technologies such as RDF, Neo4j, property graphs, or graph-based analytics is a plus.