STARK Group
Lead Data Engineer
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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.
Key Responsibilities
Data Engineering Leadership & Transformation Delivery
- 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 DataOps 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.
Data Platform and Data Product Delivery
- 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.
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Team Leadership and Capability Development
- 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.
Collaboration and Stakeholder Engagement
- 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.
Operational Excellence
- 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, governance and data management standards.
- Balance transformation initiatives alongside ongoing operational and delivery commitments.
What Success Looks Like
- A highly engaged and capable Data Engineering team with clear ownership, accountability and development plans.
- Successful adoption of Databricks and modern cloud-based engineering practices within the team.
- Strong collaboration with System Integrators, resulting in effective knowledge transfer and growing internal capability.
- Delivery of reliable, scalable and well-documented data pipelines and data products.
- Expansion of Engineering ownership from ingestion-focused delivery to end-to-end business-ready data products.
- Improved quality, consistency and trust in datasets used for reporting and analytics.
- Significant improvements in documentation, governance and platform supportability.
- Reduced operational risk through automation and the removal of manual processes.
- A strong foundation for scalable data marts, semantic models, self-service analytics and future AI initiatives.
- Positive relationships across Engineering, Analytics and business teams, with Data Engineering recognised as a trusted delivery partner.
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Skills & Experience Required
- Significant experience in Data Engineering, Data Platform or Data Warehouse roles.
- Experience leading and developing Data Engineering teams.
- Demonstrable experience leading teams through technology or organisational change.
- Hands-on expert experience with Databricks and modern cloud-based data platforms.
- SQL and data modelling skills.
- Experience designing and building scalable data pipelines and data products.
- Experience delivering or supporting data platform modernisation and migration programmes.
- Experience working alongside consultancies, System Integrators or third-party delivery partners.
- Proven understanding of data warehousing, Lakehouse architectures and modern engineering practices.
- Excellent stakeholder management and communication skills.
- Ability to balance strategic delivery responsibilities with hands-on technical leadership.
- We are not able to offer sponsorship therefore you must have the right to work permanently in the UK
Desirable
- Experience with Azure Data Lake, Azure Synapse and Informatica.
- Experience migrating from legacy ETL and reporting platforms.
- Experience developing semantic layers, business data marts and analytics-ready datasets.
- Knowledge of Power BI semantic models and analytics engineering concepts.
- Experience implementing DataOps, CI/CD and automated testing frameworks.
- Experience working within retail, distribution, manufacturing or supply chain environments.
- Familiarity with ERP data structures and commercial domains including sales, pricing, margin, inventory and customer analytics.
Why Join?
- Play a leading role in STARK UK's significant data transformation programme.
- Lead a team through the adoption of modern data engineering technologies and practices.
- Be part of the journey to a Databricks-centric Data & Analytics platform.
- Help establish trusted, scalable data products that will power analytics, AI and automation initiatives across the business.
- Work with experienced leaders and transformation partners while making a tangible impact on the future of data and data-driven decision making at STARK UK.
- Contribute to the development of a modern, business-focused Data Engineering capability supporting multiple brands and business units.
What’s in it for you?
- Competitive Base salary
- Hybrid Working – 4 days at our Huddersfield office and 1 day WFH. You MUST be prepared to work in the office to lead a team. Fully remote working is not an option.
- Discretionary bonus
- Retirement savings plan
- Life assurance
- Enhanced maternity/paternity/adoption leave for anyone expecting or adopting a child
- A wide range of voluntary benefits including holiday buying, discounted gym membership, car salary sacrifice scheme, Cycle2Work, Benenden Healthcare and more.
- Access to a wealth of health and wellbeing services including access to online GP appointments and mental health support.
- WorkPerks – A platform home to hundreds of all your favourite high street and online discounts via the provider Reward Gateway.
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