Senior Analytics Engineer
MOO
Overview
In this role you own analytical domains end-to-end, defining metrics in a governed semantic layer and ensuring consistent, trusted answers across dashboards and AI-enabled outputs. You will model data with dbt and collaborate with stakeholders across operations, finance, and supply chain to unlock analytic capabilities. You’ll deliver insights through Tableau and contribute to a data-literacy-first culture. This is a chance to shape how data drives decisions at a fast-growing, sustainability-minded brand.
Pay / Benefits- 25 days holiday
- matched pension scheme
- paid parental leave
- private healthcare
- life insurance
- season ticket loan for commuting
- Design data models and metrics with stakeholders to enable analytics
- Define metrics, dimensions, and business logic in the semantic layer (dbt Semantic Layer / Snowflake semantic views)
- Deliver BI reporting (Tableau) with a tool-agnostic mindset and reduce output duplication
- Curate and validate governed datasets and semantic models for AI/natural-language consumption
- Promote self-service data literacy and trusted outputs across the business
- Review peers' work and contribute to modelling standards
- Demo new features and train business stakeholders as needed
- Strong SQL and production dbt experience
- Production experience on a cloud data warehouse with Git-based, review-first workflows
- Track record of defining metrics with stakeholders and delivering reliable outcomes
- Judgement on where logic should reside (semantic layer vs BI layer)
- Demonstrable interest in data analytics evolution with AI and capability development
- Excellent communication to explain technical concepts to non-technical stakeholders
- Strong business acumen and instinct to align metrics with business outcomes
- Collaborative and constructive feedback style
- dbt (production)
- SQL
- Snowflake (or cloud data warehouse)
Reference: WJ-747_30304350