At a Glance
- Tasks: Shape the future of retail analytics by designing scalable data models and implementing AI solutions.
- Company: Join Retail Insight, a leader in transforming data into actionable insights for top retailers.
- Benefits: Enjoy flexible working, 25 days annual leave, and comprehensive health benefits.
- Other info: Access extensive learning resources and enjoy a supportive, inclusive work environment.
- Why this job: Make a real impact on decision-making with cutting-edge technology and innovative analytics.
- Qualifications: Proven experience in analytics engineering, advanced SQL skills, and a curiosity for AI.
The predicted salary is between 63000 - 77000 £ per year.
Help shape the future of retail analytics.
At Retail Insight, we're on a mission to help some of the world's biggest retailers and consumer goods brands make smarter decisions through data.
Our technology helps retailers improve availability, reduce waste, increase sales, and create better experiences for customers.
Behind this is a growing Data & Analytics team that transforms complex data into meaningful commercial insights.
We're now looking for a Senior Analytics Engineer to play a key role in shaping how data is modelled, governed, and delivered across our business.
This is an opportunity to combine deep technical expertise to build AI ready analytics solutions that power decision-making for both our teams and our clients.
- What you'll be doing
- Design and maintain scalable data models using dbt and SQL
- Build and maintain trusted semantic layers and metric definitions
- Explore and implement AI-powered analytics solutions, including automated insight generation and AI agents
- Partner closely with our Customer Success teams to ensure we fully understand the business problem we're looking to solve through data
- Improve the performance, efficiency, and reliability of analytics workflows
- Mentor Analytics Engineers and Analysts, helping develop technical capability across the team
- Champion governance, documentation, and quality standards
- Work across multiple stakeholders to deliver high-impact, data-driven outcomes for the business and our clients.
- Our ideal candidate
- Proven experience in analytics engineering, data engineering, or a similar role
- Advanced SQL skills, ideally working with cloud platforms such as Snowflake or Databricks
- Strong experience with dbt and modern data modelling practices
- Python skills for automation and data manipulation
- Experience working with large-scale datasets and analytical environments
- An understanding of governance, lineage, version control and data quality frameworks
- Experience with BI and visualisation platforms such as Power BI or Thought Spot
- Excellent communication skills and the ability to engage both technical and non-technical stakeholders
- Curiosity about AI, automation, and emerging technologies, with experience using AI tools or building AI-enabled solutions being a real advantage.
- Some of our extras…
- Flexible Working – Enjoy a hybrid work model (typically 2 days in the office) with flexibility based on business needs, plus a work from anywhere policy to give you freedom to explore.
- Time Off – 25 days annual leave (+ bank holidays), increasing with length of service, plus an extra day off for your birthday!
We also operate summer hours so you can make the most of the sunshine.
- Learning & Development – Access a vast range of courses through our learning platform and benefit from structured career progression plans to support your growth.
- Health & Wellbeing – Private Medical Insurance, a healthcare cash plan, and mental health support via
Plus, we’ll ensure you have a safe and productive home setup with a workspace assessment.
- Giving Back – Take paid volunteer days to support your local community, donate to your chosen charity through salary sacrifice (we’ll match it!), and make a difference with Give as You Earn.
- Extra Perks – A car purchase scheme to make buying a new car easier, plus access to additional benefits through our online platform, including gym discounts.
Plus much more!
- Our interview process typically consists of 3 stages
- Hiring Manager intro call
- Skills Assessment
- Values based Interview
Be your authentic self - Retail Insight is committed to promoting equal opportunities in employment.
All employees and any job applicants will receive equal treatment.
We actively seek to create an environment where everyone feels respected, supported, and encouraged to contribute their best work.
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Senior Analytics Engineer employer: Retail Insight
Retail Insight is an exceptional employer that fosters a culture of innovation and collaboration in the heart of London. With a strong emphasis on employee growth, we provide opportunities for mentorship and skill development, particularly in cutting-edge technologies like AI-driven testing. Our hybrid working model ensures a healthy work-life balance while being part of a dynamic team dedicated to elevating quality engineering practices.
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We think this is how you could land Senior Analytics Engineer
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Retail Insight.
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We think you need these skills to ace Senior Analytics Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Craft a Tailored Cover Letter:For a full-time role at Retail Insight, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Retail Insight. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Retail Insight
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Retail Insight!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
