Data Engineering Manager

Responsibilities We are seeking an experienced Data Engineering Manager to lead the design, development, and delivery of scalable data platforms and data products that power personalized customer experiences across digital retail channels. This leader will manage and develop a team of Data Engineers responsible for building reliable, secure, and high-performance data pipelines, machine learning data infrastructure, and customer data solutions that enable personalized product search, search ranking, recommendations, customer segmentation, behavioral analytics, and omnichannel personalization.

As a people leader, you will be responsible for hiring, onboarding, coaching, performance management, succession planning, and career development while fostering a culture of innovation, operational excellence, and continuous improvement. You will partner closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience, and senior technology leaders to deliver strategic initiatives that drive measurable business outcomes. The ideal candidate combines deep expertise in modern data engineering and large-scale data platforms with proven leadership experience and a strong understanding of customer behavior data, personalization systems, recommendation engines, and cloud-based technologies.

Lead, mentor, and develop a high-performing team of Data Engineers across one or more engineering squads. Foster an environment of accountability, collaboration, innovation, and customer-centric thinking. Manage all people leadership responsibilities, including hiring, onboarding, performance reviews, career development, promotions, succession planning, compensation planning, and employee engagement. Coach and mentor engineers in engineering best practices, technologies, processes, and career growth. Empower team members to be autonomous, highly effective, and capable of delivering scalable solutions.

Establish engineering standards, coding practices, operational excellence frameworks, and delivery processes. Drive Agile planning, sprint execution, prioritization, and delivery of strategic initiatives.

Lead the design, development, and operation of scalable batch, streaming, and real-time data platforms.

Develop and maintain data products supporting:

• Personalized product search
• Search relevance and ranking optimization
• Product recommendations
• Customer segmentation
• Customer identity and house holding
• Behavioral analytics
• Omnichannel personalization

Design scalable data architectures utilizing modern lakehouse, data lake, and cloud-native patterns. Build and support feature stores, APIs, and data services used by machine learning and personalization systems. Ensure high levels of data quality, reliability, observability, governance, security, and compliance. Optimize platform performance, scalability, availability, and cost efficiency. Implement monitoring, alerting, SLA management, and incident response procedures for production data platforms.

Develop technical roadmaps aligned with business priorities and long-term organizational objectives. Lead the technical design and delivery of complex initiatives across multiple systems and platforms. Recommend improvements to architecture, scalability, reliability, security, performance, and operational processes. Evaluate emerging technologies and industry best practices to enhance platform capabilities. Guide engineering teams on architectural decisions, code quality, design reviews, and technical standards. Assist in diagnosing and resolving highly complex technical and operational issues.

Build foundational data capabilities that support:

• Product recommendation engines
• Customer 360 platforms
• Customer identity resolution
• Clickstream analytics
• Purchase behaviour analysis
• Real-time personalization
• Search relevance optimisation
• Behavioural event processing

Partner with Data Scientists and Machine Learning Engineers to operationalize and scale personalization models. Enable experimentation, A/B testing, feature engineering, and measurement frameworks that improve customer experiences.

Collaborate closely with Product Management, Data Science, Machine Learning Engineering, Search Engineering, Customer Experience teams, and business stakeholders. Translate business objectives into scalable technical solutions and execution plans. Communicate technical strategy, progress, risks, recommendations, and outcomes to leaders and stakeholders. Lead cross-functional initiatives with significant business impact and organisational visibility.

Establish operational objectives, work plans, staffing strategies, and resource allocations. Ensure adherence to budgets, timelines, and performance requirements. Implement strategic policies, processes, and…