Analytics Engineer
Role overview:
Analytics Engineer
Waterloo - Hybrid Working
Full Time
Permanent
Grade 4
At Currys we’re united by one passion: to help everyone enjoy amazing technology. As the UK’s best-known retailer of tech, we’re proud of the service our customers receive – and it’s all down to our team of 25,000 caring and committed colleagues. Working as one team, we learn and grow together, celebrating the big and small moments that make every day amazing.
Currys is in the middle of one of the most ambitious AI and automation shifts in UK retail. We are rethinking how customers discover and buy technology, how stores operate, how supply chains move, and how colleagues do their best work. We’re reshaping how the business trades, plans and serves.
The AI & Monetisation function is where the boldest bets get placed.The squad you join is greenfield, built around a real business domain, and backed by senior sponsorship. You will own that domain end to end, set the roadmap with the stakeholders who run it, and ship products that move the numbers in the P&L.
These problems are genuinely hard: optimising stock availability, automating complex operating processes, putting useful AI into the hands of frontline colleagues, and monetising the audience and data we already have. You will be a change agent in a business moving fast and willing to back people who can move with it.
Role overview:
- Develop and maintain dbt models that transform raw data into trusted datasets for analytics and business intelligence
- Implement data quality tests and monitoring to ensure accuracy and reliability
- Optimise query performance using effective data modelling and materialisation strategies
- Establish and maintain documentation and data dictionaries for analytical models, KPI definitions and metrics frameworks
- Support self-service analytics by building reusable, high-quality data models
- Collaborate with cross-functional teams to translate business requirements into technical solutions
- Collaborate with data engineers to define requirements for new data sources and pipelines
- Conduct exploratory data analysis to identify trends, patterns, and anomalies in business performance
- Build interactive dashboards and reports that empower self-service analytics
- Design visualizations that clearly communicate complex data stories to both technical and non-technical audiences
What you'll bring:
- Strong SQL skills with experience in complex data transformations, CTEs, and window functions
- Expertise with dbt and modern analytics engineering tools
- Solid understanding of dimensional modelling and data warehousing concepts
- Experience with Git-based workflows for version control and collaboration for analytics
- Knowledge of data testing frameworks and quality assurance practices
- Experience with Snowflake, Databricks, or similar data platforms
- Proficiency in Omni, Looker or similar BI tools (Tableau, Power BI)
- Strong analytical thinking and problem-solving abilities
- Excellent communication skills with ability to present findings to diverse audiences
Experience Required:
- 2-4 years of experience in a data analyst or analytics engineer role
- Degree in Computer Science, Analytics, or a related technical field highly desirable
- dbt & Analytics platform certification beneficial
Why join us:
Join our team and we'll be with you every step of the way, helping you develop the career you want with new opportunities, on-going training and skills for life.
Not only can you shape your own future, but you can help take charge of ours too. As the biggest recycler and repairer of tech in the UK, we’re in a position to make a real impact on people and the planet.
Every voice has a space at our table and we're committed to making inclusion and diversity part of everything we do, including how we strengthen our workforce. We want to make sure you have a fair opportunity to show us your talents during our application process, so if you need any additional assistance with your application please email [email protected] and we'll do our best to help.
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