We’re the Moonpig Group – home to Moonpig, Greetz, Red Letter Days and Buyagift – and we’re on a mission to make people feel loved, celebrated and remembered. Whether it’s a card that gets them laughing out loud or a gift that makes their day, we help people stay close, no matter the miles.
We’re proud to be leading the online gifting revolution, with brilliant products, clever tech and a whole lot of heart. Our platform makes it easy to create moments that matter – packed with personal touches and delivered with care.
We’re not just about selling cards or gifts – we’re here to spread joy, spark smiles and make every celebration feel extra special. And with values that guide how we work and support one another, we’ve built a place where people (and ideas) can truly thrive.
If you’re looking to make an impact, bring your spark and be part of something meaningful – we’d love to have you on the team.
London – Hybrid | Competitive Salary + Benefits

WANT TO KNOW MORE?

Explore our full benefits package: here
Check out our podcast, tech blog and product blog to hear more about how we work and what we’re building!

ABOUT THE ROLE

At Moonpig, we’re all about making moments that matter – and data is at the heart of how we do that. As an Analytics Engineer, you’ll play a key role in turning raw data into reliable, well-modelled datasets that power insights, experimentation, and smart decision-making. Sitting in our Data Platform Team, you’ll be bridging the gap between data engineering and analytics, partnering with teams across Product, Marketing, and Engineering to make sure the right data is accessible, accurate, and actionable.
You’ll shape how we build and maintain transformation pipelines, support self-serve analytics, and help scale our data infrastructure so we can keep delivering meaningful customer experiences at pace.

KEY RESPONSIBILITIES:

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• Build scalable and reusable data models using dbt and Snowflake

• Own and optimise transformation pipelines, ensuring performance and cost-efficiency
• Develop data quality checks and monitoring using tools like Metaplane
• Collaborate with BI, Data Science, and Engineering teams to define requirements and deliver impactful datasets
• Document data models and promote best practices in analytics engineering
• Explore and integrate new tools (like Dagster) to improve scalability and workflow orchestration