Data Engineering Manager

We don’t think we’re exaggerating when we say we work with one of the most exciting customer data sets in UK retail.

We sit within Customer & Channels and own the Digital Customer Interactions Data domain. We ingest, model and provision behavioural data from Sainsbury’s, Argos, Nectar, Habitat, Tu, SmartShop and other digital channels into our cloud data platform, enabling data-driven decision making across marketing, analytics, data science, customer insight and reporting.

Our products provide near real-time and batch digital interaction data to a wide range of business capabilities, including CRM, CDP, Nectar360, SmartShop, customer journey analytics and strategic transformation programmes. We operate at the heart of the customer data ecosystem, creating trusted data products that are consumed across multiple teams and business units.

Working in an inclusive, agile and collaborative environment, you’ll have the space to solve complex engineering challenges, influence strategic decisions and help shape how customer interaction data is used across one of the UK’s largest retailers.
 

As a Data Engineering Manager, you will lead a multi-skilled data engineering team responsible for delivering scalable, governed and high-performing data products within the Digital Customer Interactions domain.

You will:

• →Lead a team of Data Engineers, Analytics Engineers, Architects and associated engineering specialists to deliver innovative and reliable data products that create measurable business value.
• →Own product delivery end-to-end, covering both change and run activities, including service management, reliability, operational support, governance and continuous improvement.
• →Drive the technical direction and engineering strategy for customer interaction data products, ensuring solutions are scalable, secure, supportable and aligned with enterprise architecture standards.
• →Lead engineering delivery across cloud data platforms, data ingestion frameworks, orchestration platforms, streaming solutions and modern data engineering patterns.
• →Oversee the design, development and operation of data pipelines that deliver trusted customer interaction data into analytical and operational platforms across the organisation.
• →Collaborate closely with Product Managers, Data Architects, Governance, Analytics, Data Science, Security and business stakeholders to shape roadmaps, prioritise demand and deliver strategic outcomes.
• →Provide leadership for high-profile programmes and cross-functional initiatives, balancing strategic investment, technical debt reduction, platform sustainability and business priorities.
• →Own resource planning, capacity management and prioritisation across BAU support, roadmap delivery and strategic transformation programmes, making trade-offs, risks and dependencies clear.
• →Ensure robust governance, privacy, security and data quality standards are embedded across all products, including data lineage, access management, PII handling, compliance requirements and operational controls.
• →Recruit, retain, coach and develop talented engineers while fostering an inclusive, collaborative and high-performing engineering culture.
• →Establish and promote engineering best practice across software engineering, data engineering, DevOps, automation, testing, observability and operational excellence.
• →Manage product and engineering budgets, support financial planning activities and actively seek opportunities for cost optimisation and value realisation.
• →Build strong relationships with senior stakeholders and provide clear communication of delivery progress, risks, opportunities and strategic recommendations.
   

You are an experienced technology leader with a passion for building high-performing engineering teams and delivering trusted, scalable data products that drive meaningful business outcomes.

You have:

• Proven experience leading Data Engineering teams in complex, enterprise-scale environments.
• Strong understanding of modern data architecture, cloud platforms and large-scale data product delivery. Experience with technologies such as Snowflake, AWS, GCP, data orchestration platforms and modern ELT/ETL frameworks is highly desirable.
• Experience operating and evolving critical data platforms that support analytical, operational and customer-facing use cases.
• Strong stakeholder management skills and the ability to influence decisions across engineering, product, architecture, governance and senior business stakeholder groups.
• A track record of balancing delivery demands, technical excellence, operational stability and team wellbeing within a fast-paced environment.
• Strong commercial awareness and the ability to evaluate engineering investment decisions based on business outcomes, cost and risk.
• Experience managing engineering capacity, prioritisation and delivery dependencies across multiple concurrent initiatives.
• A strong understanding of data governance, security, privacy and compliance principles, and the ability to embed these practices into day-to-day engineering delivery.
• Excellent people leadership skills, with demonstrated success in coaching, mentoring, developing and inspiring engineering talent.
• Experience driving adoption of Agile, Lean and modern engineering practices to improve team effectiveness and delivery outcomes.
• A growth mindset, curiosity and a passion for continuous improvement, always looking for better ways to solve problems and create value for customers and colleagues.

• Proven experience leading Data Engineering teams in a complex enterprise environment, including people management, performance development, resource planning, prioritisation and delivery leadership.
• Strong technical background in modern data engineering, with experience delivering and operating large-scale data platforms, data pipelines, cloud-based data solutions and data products.
• Demonstrable experience managing end-to-end ownership of data products or platforms, balancing delivery, operational support, reliability, governance, technical debt and continuous improvement.
• Strong stakeholder management and influencing skills, with experience working across Product, Architecture, Analytics, Data Science, Security and senior business stakeholders to shape priorities and drive outcomes.
• Experience building and developing high-performing engineering teams, including coaching, mentoring, recruitment, creating an inclusive culture and driving engineering best practices.