Analytics Engineer - Currys

Location: Waterloo, London (Hybrid - 2-3 days per week in office)
Contract: 12-Month Contract (Strong likelihood of conversion to permanent)
Rate: £400 per day (Inside IR35)

The Opportunity

We are seeking an experienced Analytics Engineer to join a growing data team, helping to transform raw and complex data into trusted, business-ready datasets and insights. This role is ideal for someone with a strong analytics background who enjoys working closely with stakeholders, building robust data models, and enabling self-service analytics across the organisation.

This is a highly analytics-focused position with minimal pipeline engineering responsibilities. We are looking for someone who can hit the ground running with strong SQL, dbt, data modelling, BI, and stakeholder management experience.

Key Responsibilities

Analytics Engineering & Data Modelling

• Develop and maintain dbt models that transform raw data into trusted datasets for analytics and business intelligence.
• Design, build, and maintain scalable analytical data models using modern data warehousing principles.
• Work with unconformed and complex source data to create reliable, business-ready datasets.
• Optimise query performance through effective modelling, materialisation strategies, and best practices.
• Support self-service analytics by building reusable, high-quality data assets.

Data Quality & Governance

• Implement data quality tests, validation processes, and monitoring frameworks.
• Conduct QA activities to ensure data accuracy, consistency, and reliability.
• Create and maintain documentation, data dictionaries, KPI definitions, and metric frameworks.

Business Intelligence & Analytics

• Conduct exploratory data analysis to identify trends, opportunities, anomalies, and business performance insights.
• Build interactive dashboards, reports, and visualisations that support data-driven decision making.
• Design clear and compelling visualisations for both technical and non-technical audiences.
• Present findings and recommendations to stakeholders across the business.

Stakeholder Collaboration

• Partner with business teams to gather requirements and translate them into technical solutions.
• Collaborate with Data Engineers to define requirements for new data sources and enhancements.
• Work closely with cross-functional teams to deliver scalable analytical solutions.

Required Skills & Experience

Technical Skills

• Strong SQL skills, including complex transformations, CTEs, window functions, and query optimisation.
• Hands-on experience with dbt in a production environment.
• Strong understanding of dimensional modelling and data warehousing concepts.
• Experience building analytical models from unconformed or disparate data sources.
• Experience implementing data quality testing and QA processes.
• Experience using Git-based workflows for version control and collaboration.
• Experience with modern cloud data platforms such as Snowflake, Databricks, or similar.
• Proficiency in BI and visualisation tools such as Looker, Tableau, or Power BI.

Business & Communication Skills

• Strong analytical and problem-solving abilities.
• Excellent stakeholder management and communication skills.
• Experience presenting insights and recommendations to business audiences.
• Ability to balance technical delivery with business requirements.

Experience Required

• 2-4 years' experience in an Analytics Engineer, Data Analyst, BI Developer, or similar analytics-focused role.
• Demonstrable experience delivering end-to-end analytical solutions, from data modelling through to reporting and visualisation.
• Degree in Computer Science, Data Analytics, Mathematics, Engineering, or a related field is highly desirable.

Desirable Qualifications

• dbt Certification.
• Analytics platform certifications (Looker, Tableau, Power BI, etc.).
• Experience working within a modern data stack environment.

Ideal Candidate Profile

The successful candidate will have a strong analytics mindset and be comfortable working across data modelling, reporting, stakeholder engagement, and Business Intelligence delivery. They will have extensive experience building data models in dbt, creating trusted datasets from complex source systems, and delivering insights through BI tools such as Looker or Tableau.

This is not a data engineering role; there will be minimal, if any, pipeline engineering. The focus is on analytics engineering, data modelling, quality assurance, reporting, and enabling business users through trusted data products.