Title:  Data Platform Lead

Role Purpose 

As Team Lead, you will be a hands-on technical leader for a team of data engineers, spending much of your time designing and building our data platform architecture yourself. You will define how data is ingested, governed and modelled, setting the technical direction the team follows, while also coaching and supporting the engineers around you. Additionally, you will work closely with architecture, product and governance stakeholders to keep the platform consistent, well governed and built to last. This is a role for an experienced engineer who wants to keep building while helping others grow. 

Responsibilities 

• Design and build core parts of our data platform architecture, including ingestion, data modelling and governed data products. 

• Define technical standards and patterns for data ingestion, transformation and canonical data modelling across the team. 

• Lead architectural decisions on how the team's platform work fits into our wider data governance and privacy framework. 

• Stay hands-on: write code, review pull requests, and directly contribute to key platform components. 

• Guide the team's approach to data quality, lineage and access control, ensuring consistent, well-governed data products. 

• Provide day-to-day technical leadership and coaching to the team, helping engineers grow their skills and confidence. 

• Plan and prioritise the team's technical roadmap, balancing new capability with maintenance and technical debt. 

• Partner with business and other tech teams to translate business needs into technical design decisions. 

• Support hiring and onboarding, helping new engineers ramp up quickly on the platform's architecture. 

• Champion strong engineering practices across the team, including code quality, testing and documentation. 

Requirements 

• Hands-on expertise designing and building enterprise data platforms, ideally using Databricks or a comparable lakehouse architecture.
• Deep knowledge of data ingestion, canonical/conformed modelling, and reusable data products.
• Strong command of governance, quality, lineage, access control, security, privacy, and anonymisation practices in regulated environments.
• Ability to define architectural direction and drive adoption across engineering teams.
• Track record of mentoring engineers through technical coaching and code reviews while remaining hands-on.
• Comfortable operating as a player-coach, balancing platform delivery with team leadership.
• Knowledge of data mesh and federated data product architectures.
• Proficiency with cloud-native data ecosystems and modern engineering tooling.
• Ability to communicate technical concepts and design decisions to both technical and non-technical audiences.
• Pragmatic approach to balancing engineering excellence, execution speed, and team growth.
• Expertise in REST and GraphQL API design, schema governance, contract management, and versioning.
• Proficiency in Python and/or Scala, SQL, and Infrastructure as Code (Terraform preferred).
• Familiarity with knowledge graph technologies is good to have (including RDF, property graphs, Neo4j, and graph-based analytics)