Analytics Engineering Lead

Moonpig; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Competitive pay

Pension plan

Private healthcare (UK)

Hybrid working

Generous holidays

Learning allowances

Job summary

Moonpig Group is seeking a Lead Analytics Engineer in London on a hybrid basis (1-2 days in the office per week). You will shape data models, governance, and consumption across the business, partnering with Product, Marketing, Finance, and Engineering to deliver scalable data products.

You’ll mentor engineers, define standards, and help evolve the data platform with a focus on performance, cost efficiency, and reliability. The role offers competitive pay and benefits.

Qualifications

• Advanced SQL expertise with data modelling and performance optimisation.
• Experience designing scalable data models using dbt and cloud data platforms.
• Proficiency in Python for automation and data processing.
• Strong knowledge of Git and collaborative software development practices.

Responsibilities

• Lead analytics engineering initiatives across business domains.
• Own scalable data models and datasets, coordinating with other engineers.
• Partner with Product, Marketing, Finance, and Engineering to define requirements.
• Promote best practices in data modelling, testing, documentation, and governance.
• Design and implement scalable data models using dbt and Snowflake.
• Lead architectural decisions balancing performance, cost, and usability.
• Mentor and coach analytics engineers and promote platform standards.

Skills

SQL

dbt

Snowflake

Python

Data modelling

Git

Stakeholder mgmt

Tools

Dagster

Fivetran

DataDog

Tableau

GitHub

AWS

Terraform

Job description

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.

Lead Analytics Engineer | London - Hybrid (1-2 days per week) | Competitive Salary + Benefits

About the Role

At Moonpig Group, data powers how we create personalized experiences, make better decisions, and drive growth. As a Lead Analytics Engineer, you'll play a key role in shaping how data is modeled, governed, and consumed across the business.

Operating at a business domain level, you'll combine deep technical expertise with commercial thinking to define, prioritise, and deliver analytics engineering solutions that enable scalable, trusted, and actionable data. You'll work closely with stakeholders across Product, Marketing, Finance, Engineering, Data Science, and the wider Data team, helping turn complex challenges into high-impact data products.

As a technical leader within Analytics Engineering, you'll help set standards, mentor others, and influence the future direction of our data platform. This is an opportunity to make a meaningful impact on how Moonpig uses data to innovate, personalize customer experiences, and scale effectively.

Key Responsibilities:

• Lead the planning and delivery of analytics engineering initiatives across business domains, aligning work with strategic priorities.
• Own the delivery of scalable data models and datasets, coordinating contributions from other engineers where required.
• Partner with stakeholders across Product, Marketing, Finance, Data Science, and Engineering to define requirements and shape solutions.
• Challenge and influence stakeholders to drive scalable, sustainable, and high-impact data solutions.
• Act as a technical leader for analytics engineering, promoting best practices in data modelling, testing, documentation, and governance.
• Design and implement scalable, reusable data models using dbt and Snowflake.
• Lead architectural decisions, balancing performance, cost, scalability, and usability.
• Contribute to the evolution of analytics engineering standards, tooling, and data platform capabilities.
• Make and own technical decisions, balancing trade-offs between speed, scalability, and cost.
• Ensure high standards of data quality through testing, monitoring, and governance practices.
• Use metrics such as data quality, pipeline performance, and adoption to drive continuous improvement.
• Identify opportunities to optimise processes, tooling, and workflows.
• Translate complex business and data challenges into scalable data models and actionable delivery plans.
• Advocate for best practices in data modelling, governance, and data usage across the organisation.
• Represent Analytics Engineering in cross-functional discussions, helping teams navigate priorities and trade-offs.
• Mentor and support analytics engineers through code reviews, pairing, and knowledge sharing.
• Contribute to raising the overall quality, consistency, and maturity of the analytics engineering function.
• Support the optimisation and scalability of the Snowflake data platform, ensuring performance, security, and cost efficiency.
• Evaluate and introduce new tools and technologies that improve platform capability and engineering effectiveness.
• Drive adoption of standardised, well-documented data models across the business.

About You:

• Extensive experience in analytics engineering, data modelling, or related data disciplines, with a proven track record of operating across complex business domains.
• Advanced SQL expertise, including complex data modelling, transformation, and performance optimisation.
• Strong experience designing and maintaining scalable data models using dbt.
• Proven experience working with Snowflake and modern cloud-based data platforms.
• Deep understanding of analytics architecture, data governance, and scalable data design principles.
• Experience writing clean, efficient Python code for automation and data processing.
• Strong knowledge of Git and collaborative software development practices.
• Ability to influence stakeholders and build strong cross-functional relationships.
• Experience operating with autonomy and making decisions in ambiguous environments.
• Passion for mentoring, coaching, and developing other engineers.
• Comfortable working within agile delivery environments.
• Curiosity for emerging technologies, tools, and best practices within the data ecosystem.
• Experience with DataDog, Dagster, Fivetran, or Tableau would be beneficial but is not essential.

Our Tech Environment:

• Data Stack: Snowflake, dbt, SQL, Python, Fivetran, Dagster, DataDog, Tableau.
• Infrastructure: AWS (SageMaker, EC2, Lambda, Glue, S3), Terraform, API Gateway.
• Collaboration Tools: GitHub, Jira, Confluence.
• Analytics Tools: GA4, GTM, GCP BigQuery.

How we get there:

• Recruiter Screening Call
• Hiring Manager Interview
• Technical Test
• Final Interview with Wider Team Members

Our process may vary depending on role and availability. We keep candidates informed of any changes.

What's in it for you?

We believe in empowering our team to do their best work. Enjoy:

• Competitive Pay & Bonuses: Plus, generous pension plans & staff discounts.
• Wellbeing First: Private healthcare (UK) and mental health support
• Flexible Working & Time Off: Generous holidays, hybrid working (1-3 days in office, depending on role/team) & up to 20 days of international working.
• Career Growth: Learning allowances, coaching & development programs.

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!

Our Ways of Working:

We trust our colleagues to do what's right and offer flexibility to support a balance between work and life. At the same time, face-to-face office time is an important and expected part of working at Moonpig Group. We believe regular in-person working supports collaboration, alignment, and effective decision-making. Candidates will have regular and ongoing time working from the office as part of their role, which will be discussed during the recruitment process.

Moonpig Group's Commitment to Equality, Diversity, and Inclusivity:

At Moonpig Group, we're all about creating a workplace where everyone feels they truly belong. We celebrate what makes each of us unique, whether that’s our background, how we work best, or what matters most to us.

From working parents who need flexible hours to neurodiverse colleagues with specific working styles, we're here to support our people in ways that work for them. Because when you feel valued and included, you can thrive, and so can we.

We're proud to have a number of employee‑led groups driving this forward, including our LGBTQ+, Gender Balance, Neurodiversity and EMBRACE (Educating Myself for Better Racial Awareness and Cultural Enrichment) communities, plus our Group-wide EDI committee. These teams help make sure every voice is heard and every idea has a place.

We know that diversity fuels creativity, innovation and connection, and that’s why we'll keep pushing for progress. Together, we're building a culture where everyone feels safe, supported, and free to be their brilliant, authentic selves.

We believe in a workplace that supports and celebrates all workers. If you have a preferred name, please use it to apply and share your pronouns if you are comfortable to do so. If you have any reasonable adjustment requests throughout the interview process please let us know on your application or speak to the recruiter.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.