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About the Role

The Analytics Engineer is responsible for delivering enterprise dashboards, operational reports, KPI views, and business visualisations. This role translates business requirements and data product definitions into accurate, well-designed, and maintainable reporting solutions, applying strong visual design judgement and sound engineering practices.

Responsibilities

Design, build, and maintain enterprise reports, dashboards, and visualisations using approved reporting and data platforms, including Tableau and Databricks SQL.
Translate business requirements into technically robust reporting outputs, ensuring solutions are accurate, maintainable, and aligned to agreed reporting standards.
Develop high-quality visual designs for dashboards and reports, ensuring outputs are intuitive, accessible, clearly structured, and appropriate for non-technical business users.
Implement KPI calculations, measures, and reporting logic across different levels of aggregation.
Document KPI logic, aggregation rules, source data, assumptions, exceptions, filters, known limitations, and business definitions.
Work with Data Product Managers to understand business outcomes, reporting priorities, and data product requirements.
Work with Data Engineers and Data Solution Architects to ensure reporting outputs are built on appropriate data models, semantic layers, certified data products, and governed data sources.
Apply reporting security and privacy controls, including role-based access, row-level security, permission management, data classification, and appropriate handling of sensitive data.
Support user acceptance testing by preparing testable outputs, resolving defects, validating calculations, and responding to prioritised feedback.
Optimise dashboard and report performance, including query efficiency, extract design, refresh logic, data source configuration, workbook structure, and visual load times.
Apply enterprise visualisation standards consistently, including naming conventions, design patterns, access controls, version management, refresh schedules, and publishing processes.
Contribute to reusable reporting assets, templates, certified datasets, and self-serve reporting components.
Maintain documentation for report specifications, data lineage, access configurations, refresh schedules, operational dependencies, and support requirements.
Support the rationalisation of duplicated, manual, or ungoverned reports by helping migrate reporting activity onto approved tools, platforms, and standards.

Requirements

Hands-on experience delivering enterprise dashboards, reports, and visualisations in a business intelligence, reporting engineering, or analytics delivery role.
Experience operating in a mid-level engineering role, taking ownership of assigned reporting outputs while working within standards and priorities set by senior data engineering and platforms leadership.
Strong practical experience with Tableau, including dashboard development, calculated fields, level-of-detail expressions, data source management, publishing, permissions, and performance optimisation.
Experience with SQL and cloud data platforms, ideally including Databricks SQL, Delta Lake, or equivalent lakehouse/warehouse technologies.
Good understanding of data modelling concepts, including facts, dimensions, joins, aggregations, semantic layers, and certified datasets.
Experience implementing KPI logic and business metrics across different levels of aggregation, with the ability to translate business definitions into reliable technical calculations.
Good understanding of reporting security principles, including role-based access control, row-level security, data classification, and handling of sensitive data.
Strong visual design judgement, with the ability to create clear, intuitive, and well-structured dashboards for non-technical users.
Experience working with data engineers, product managers, analysts, architects, and business stakeholders in cross-functional delivery environments.
Practical understanding of the reporting lifecycle, including requirements capture, build, testing, publishing, documentation, version control, and support.
Familiarity with governed data products, certified metrics, data catalogues, business glossaries, and data lineage is beneficial.
Ability to manage multiple assigned priorities by clarifying deadlines, dependencies, and trade-offs while maintaining accuracy, quality, and attention to detail.

Skills

Tableau
Databricks SQL
SQL
Cloud data platforms
Data modelling
KPI implementation
Reporting security
Visual design
Cross-functional collaboration
Reporting lifecycle management

Experience Level

Mid-level

About the Company

At Burberry, our people and culture underpin how we deliver for our customers and our brand.
We are building a high-performance culture that encourages creativity and collaboration, and enables colleagues to do their best work.
Guided by our reimagined purpose, To Embrace the Elements with Open Arms, we bring together diverse perspectives, skills and expertise to create exceptional luxury products and experiences.
Our purpose also informs the standards of behaviour we expect, how we lead and how we make decisions across the business.

Equal Opportunity

Burberry is an Equal Opportunities Employer and as such, treats all applications equally and recruits purely on the basis of skills and experience.