At a Glance
- Tasks: Lead the design of data models and ensure technical integrity for impactful analytics.
- Company: Join a forward-thinking company that values innovation and collaboration.
- Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Be part of a dynamic team with mentorship opportunities and career advancement.
- Why this job: Make a real difference by transforming business needs into actionable data insights.
- Qualifications: Expertise in SQL, data modelling, and experience with cloud platforms required.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Set and enforce the data modelling standards that govern how the team designs facts, dimensions, aggregates, and semantic layers.
- Review and exercise independent judgement on modelling approaches proposed by Lead Analytics Engineers, making formal recommendations where decisions carry material risk or long-term architectural consequence.
- Own the technical integrity of the curated data layer – ensuring what is built is correct, performant, well-documented, and genuinely fit for business use.
- Translate business requirements into data model designs that are both technically sound and analytically useful.
- Act as the final technical quality checkpoint before work reaches production or is presented to business stakeholders.
- Bring genuine analytical expertise: the ability to sit with data, identify what it is and is not telling you, and present findings in a way that is clear, honest, and actionable.
Requirements
- Deep SQL expertise, including complex transformations, window functions and performance tuning in a cloud environment.
- Proven experience designing analytical or data warehouse models.
- Strong dimensional modelling knowledge such as Kimball approaches, star schemas and aggregates.
- Experience with Databricks or similar platforms.
- Hands on ownership of curated data layers used by the business.
- Strong understanding of end-to-end data dependencies across a modern data stack (pipelines → models → semantic layer → consumption).
- Strong understanding of data quality, profiling and validation techniques.
- Mentoring and acting as a technical lead.
We think you need these skills to ace Lead Analytics Engineer
Problem-Solving Skills
SQL
Python
Data Engineering
Communication Skills
Data Governance
Automation
