IT Data Platform Engineering Manager

Salary: £44,000 - 83,000 per year

Requirements

• Significant experience in data engineering and data platform technologies, with deep knowledge of Azure data services, including Databricks, Data Factory, Data Lake, Synapse, and lakehouse architectures
• Proven track record of leading and managing technical data teams, including coaching, development, and performance management of data engineers and architects
• Solid knowledge of data architecture principles, enterprise data modelling, data integration patterns, ETL/ELT, and data pipeline orchestration
• Experience defining and executing data platform strategy and roadmaps, including platform modernisation, migration, and capability expansion
• Experience enabling AI, machine learning, and advanced analytics through robust and governed data platform services
• Experience managing third-party data engineering partners and vendor relationships, including service reviews, SLA management, and delivery governance
• Strong understanding of DataOps, CI/CD for data, infrastructure-as-code, and DevOps practices applied to data engineering
• Understanding of data security, privacy, and regulatory compliance requirements in the context of enterprise data platforms
• Knowledge of self-service business intelligence and analytics enablement, including Power BI and governed data access patterns
• Effective leadership and people management skills, with the ability to develop, motivate, and retain a high-performing technical data team
• Excellent communication and stakeholder management skills, with the ability to influence stakeholders outside of own job area regarding data policies, practices, and procedures
• Strategic and analytical thinker with the ability to translate business data needs into platform engineering priorities and actionable delivery plans
• Solid problem-solving and decision-making skills, with the ability to navigate difficult to moderately complex technical and organisational challenges
• Collaborative and inclusive leadership style, with the ability to work across functional boundaries and build effective relationships with IT and business teams
• Motivated and results-oriented, with a track record of driving continuous improvement, automation, and engineering excellence
• Ability to manage competing priorities and deliver under pressure in a fast-paced, global environment
• Commercial awareness, with the ability to manage budgets, vendor contracts, and resource allocation effectively

Responsibilities

• Lead and manage the Data Platform Engineering team, including data engineers, data architects, developers, and analytics specialists, providing coaching, development, and performance management
• Own the operational delivery and continuous improvement of the Common Data Environment platform, built on Azure and Databricks, ensuring availability, performance, and scalability
• Define, maintain, and execute the Data Platform and AI Enablement roadmap, ensuring platform capabilities evolve to support analytics, machine learning, generative AI, and future AI-enabled business services
• Provide technical direction and design authority for data engineering solutions, including data pipelines, ETL/ELT processes, data integration, lakehouse architecture, real-time data streaming, and AI-ready data architectures
• Oversee the development and operation of data platform capabilities that support AI workloads, including knowledge retrieval services, semantic models, data products, and platform integration capabilities
• Manage relationships with third-party data engineering partners, vendors, and managed service providers, including service reviews and delivery assurance
• Oversee data architecture standards, enterprise data modelling, and data domain design to ensure consistency, scalability, and alignment with enterprise architecture
• Coordinate with Cyber Security & Compliance to ensure data security, privacy, and regulatory compliance across all data platform services
• Champion DataOps and CI/CD practices for data, improving automation, reliability, and engineering excellence across the data lifecycle
• Support the delivery of self-service business intelligence and self-service data analytics capabilities, enabling business users to access and leverage governed data
• Coordinate with Cloud & Infrastructure, Platforms & Collaboration, Enterprise Applications, and Strategic Engagement teams to ensure integrated data services and aligned delivery
• Represent the Data Platform Engineering function in IT leadership forums, steering committees, and cross-functional data governance bodies
• Work with stakeholders outside of the immediate team regarding data policies, standards, and best practices, ensuring alignment with our data strategy

Technologies

• AI
• Azure
• Business Intelligence
• CI/CD
• Cloud
• Databricks
• DevOps
• ETL
• Support
• Machine Learning
• Power BI
• Security

More

We are looking for an IT Data Platform Engineering Manager to join our team in our Aberdeen office, London office or remotely on a full-time permanent contract. This is a management role responsible for the leadership, delivery, and continuous improvement of data platform engineering services across our organisation. We manage a team of experienced data professionals, including data engineers, data architects, developers, and analytics specialists, and are accountable for the strategy implementation, operational performance, and evolution of our Common Data Environment built on Azure and Databricks. Reporting to the Technical Director, the role provides technical direction and people management across our data platform team, ensuring that data engineering, data architecture, data integration, and analytics enablement capabilities are aligned to business objectives and delivered to a high standard. We also lead the development and evolution of AI-enablement capabilities delivered through our enterprise data platform, ensuring the right architecture, data readiness, platform services, and operational standards are in place to support the adoption of AI technologies across the organisation while maintaining alignment with our data governance, security, and enterprise architecture standards.

last updated 34 week of 2026