Lead Data Engineer
Overview
As a Lead Analytics Engineer, you will be responsible for designing, building, and continuously improving trusted, scalable data products that enable analytics, reporting, machine learning, and business decision-making across the organisation. You will act as a technical leader within the data team, translating complex business requirements into well-governed data models, feature marts, and data pipelines while driving best practices in analytics engineering.
Requirements
- Degree or Diploma in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, Engineering, or a related field
- Equivalent practical experience in Analytics Engineering, Data Engineering, or Data Product Development may be considered
- 6+ years' experience within Data Engineering, Analytics Engineering, Data Science, or related data environments
- Proven experience designing, building, and productionising data models, pipelines, architectures, and analytics-ready datasets
- Experience providing technical leadership, coaching, code reviews, and engineering guidance within data teams
- Experience working with cross-functional technical and business stakeholders
- Experience operating within Agile delivery environments
- Exposure to Retail, Ecommerce, Financial Services, or other large-scale digital businesses is advantageous
- Advanced SQL development, optimisation, and performance tuning
- Strong data modelling expertise
- Experience building scalable analytics data products and data pipelines
- Knowledge of data governance, metadata management, and lineage principles
- Strong understanding of testing, deployment, monitoring, and production support practices
- Experience with modern cloud-based data platforms
- Proficiency in Python, PySpark, or similar data processing technologies (advantageous)
- Experience with version control and software engineering practices
Responsibilities
- Lead the design, build, and optimisation of analytics-ready data models, data marts, feature marts, and data pipelines
- Translate complex business requirements into scalable, reusable analytics engineering solutions
- Develop trusted data products that support analysts, data scientists, machine learning teams, and business users
- Provide technical leadership throughout the analytics engineering lifecycle
- Lead code reviews, data model reviews, and solution design discussions
- Establish and drive analytics engineering standards, best practices, and governance frameworks
- Guide and mentor Analytics Engineers and broader data practitioners
- Implement and maintain data quality controls, automated testing, monitoring, and quality assurance procedures
- Ensure data products are accurate, reliable, scalable, and production-ready
- Partner with Data Engineers, Data Scientists, Analysts, and business stakeholders to refine requirements and deliver data-driven solutions
- Investigate and resolve production incidents, pipeline failures, and data-related issues
- Identify opportunities to improve tooling, automation, governance, and engineering processes
How to apply
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