Analytical Engineer

Overview

In this role you will shape trusted data models, metrics and semantic layers to empower decision-making across On the Beach. You will bridge data engineering, BI, and AI to deliver reliable analytical products used by multiple teams. You’ll ensure data is accurate, well-governed, and easy to discover, enabling future AI-enabled analytics. This is a chance to influence reporting, analytics, and data-driven decisions at scale.

Pay / Benefits

• 25 days holiday plus birthday off
• Learnerbly learning platform access
• Enhanced parental leave
• Employee Assistance Programme
• Simplyhealth health plan
• Share Incentive Plan (SIP)

Responsibilities

• Design, build, and maintain trusted analytical models, transformations and semantic definitions across core business domains
• Create clear, reusable metric definitions to establish a single source of truth
• Collaborate with Data Engineers to map refined data layers to business-ready products
• Develop and maintain dbt models, tests and documentation for reliable analytics
• Shape semantic layers supporting BI tools and AI use cases like natural language analytics and text-to-SQL
• Improve data quality through testing, monitoring, validation, and clear ownership of models
• Partner with stakeholders to translate reporting needs into scalable data products
• Support self-service analytics by improving data discoverability and usability
• Explore AI-assisted tools to enhance SQL development, testing, and documentation
• Promote data governance, lineage and trust across analytical datasets
• Communicate with both technical and non-technical audiences
• Make pragmatic decisions balancing quality, usability and delivery in a fast-moving environment

Key requirements

• Strong SQL skills with production-grade analytical data modeling experience
• Data modeling approaches such as dimensional modeling and star schemas
• Experience with dbt or similar transformation/orchestration tools
• Experience building semantic models for BI or self-service analytics
• Experience in cloud data environments (Databricks, BigQuery, Snowflake)
• Engineering practices in analytics (Git, PRs, testing, documentation, CI/CD)
• Improving data quality, lineage, governance and trust across datasets
• Ability to collaborate with analysts, engineers, product teams and stakeholders
• Clear communication to both technical and non-technical audiences
• Pragmatic, fast-moving mindset balancing quality and delivery

• Clear communication
• Cross-functional collaboration
• Problem solving
• dbt
• Dimensional data modeling
• SQL

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