Lead Data Engineer

We're proud to be part of STARK Building Materials UK and dedicated to providing top-quality products and exceptional service to our customers. We're a friendly and collaborative team, passionate about what we do and committed to doing it well.

STARK UK is transforming its data platform and engineering capability to support the next generation of analytics, self-service reporting, AI, automation and data-driven decision making.

We are seeking a highly capable, hands-on Lead Data Engineer to lead our Data Engineering team through a significant period of technology, capability and organisational change.

Reporting to the Head of Data Engineering, you will play a pivotal role in delivering our transition from Informatica and Azure Synapse-based solutions to a modern Databricks-centric platform. You will lead a team of Data Engineers while working closely with Data Analysts, business stakeholders and System Integration partners to build scalable, trusted and reusable data products.

This role combines technical leadership, people leadership and delivery management. You will inherit an established team with deep business knowledge and support their development into a modern Data Engineering capability, helping them adopt new technologies, practices and responsibilities.

As part of our transformation, Data Engineering is evolving from a traditional focus on ingestion and transformation into ownership of the full data product lifecycle. This includes Bronze, Silver, Gold and Platinum data assets, semantic models, business-facing datasets and the engineering foundations that enable trusted analytics across STARK UK.

This is an opportunity to make a lasting impact on a growing function while helping shape how data is engineered, governed and consumed across the business.

• Deliver the Data Engineering roadmap in partnership with the Head of Data Engineering.
• Lead the engineering team through the transition from Informatica and Synapse-based solutions to Databricks.
• Establish and embed modern engineering practices that improve quality, scalability, maintainability and operational resilience.
• Support the adoption of Data Ops practices, automation, testing, monitoring and deployment standards.
• Work closely with System Integrators and third-party partners, ensuring effective delivery while developing internal capability and reducing long-term dependency on external resources.
• Drive continuous improvement across engineering processes, tooling, governance and ways of working.
• Support the successful delivery of change across people, technology and process.

• Lead the design, development and maintenance of scalable data pipelines and data products.
• Oversee ingestion, transformation and curation of data from multiple operational systems and external sources.
• Ensure data products are reliable, performant and fit for business consumption.
• Support the evolution of the Data Lakehouse architecture across Bronze, Silver, Gold and Platinum layers.
• Improve data quality, lineage, documentation and discoverability across the platform.
• Partner with the Insight and Analytics team to ensure data products effectively support reporting, self-service analytics and future AI initiatives.
• Contribute to the development and improvement of semantic models, business data marts and reusable datasets.
• Support the migration from legacy BI tooling through the creation of trusted data structures and business-ready data products.

• Lead, coach and develop a team of Data Engineers through a period of significant technology and organisational change.
• Build a culture of ownership, accountability, continuous improvement and knowledge sharing.
• Develop capability plans that align individual growth with the future requirements of the platform.
• Support engineers in developing expertise in Databricks, modern cloud data engineering and contemporary engineering practices.
• Establish clear standards, responsibilities and performance expectations across the team.
• Manage performance, development and career progression of team members.
• Support recruitment, onboarding and team expansion where required.

• Develop strong relationships across technology and business functions.
• Translate technical concepts into clear business outcomes for non-technical stakeholders.
• Facilitate effective collaboration between engineering, analytics, architecture and operational teams.
• Contribute to planning and prioritisation activities across the data function.

• Ensure the ongoing reliability, stability and supportability of data platform services.
• Drive improvements in monitoring, alerting and operational processes.
• Reduce key-person dependencies through effective documentation and knowledge management.
• Identify and address technical debt within existing solutions.
• Ensure engineering activities comply with security,…