Analytics Engineer

Moonpig Group

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 personalised experiences, make better decisions, and drive growth. As a Lead Analytics Engineer, you'll play a key role in shaping how data is modelled, 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, personalise customer experiences, and scale effectively.

Valtech

Why Valtech? We’re the experience innovation company - a trusted partner to the world’s most recognised brands. To our people we offer growth opportunities, a values-driven culture, international careers and the chance to shape the future of experience.  THE OPPORTUNITY At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.  We are proud of:  * The work we do and the innovation we drive  * Our values of share, care and dare  * A workplace culture that fosters creativity, diversity and autonomy  * Our borderless, global framework, which enables seamless collaboration  THE ROLE   We’re looking for a Conversational Analytics Engineer with strong expertise across the Google Cloud Platform ecosystem to drive forward conversational analytics and AI solutions.  This role blends hands-on engineering, AI/ML innovation and client-facing problem solving. You’ll work across traditional data engineering and emerging LLM / agentic AI patterns, helping design and deploy scalable, production-ready solutions.  Role responsibilities Data Engineering, AI & Delivery  * Design and build scalable data solutions using BigQuery and GCP-native tooling  * Develop and deploy ML and AI solutions, including LLM-based and agentic systems   * Work with tools such as Gemini to power conversational and analytical use cases   * Build and integrate analytical agents into real-world applications   * Implement evaluation frameworks (version-controlled via Git) to assess model and system performance   * Orchestrate APIs and enable seamless integration between models, data pipelines, and applications   * Apply modern MLOps and engineering best practices to deploy and maintain solutions in production   * Define and assess the quality and timeliness of available data sources  Problem Solving & Client Engagement  * Translate business challenges into scalable data and AI solutions   * Communicate complex technical concepts clearly to non-technical stakeholders   * Lead client conversations to shape data and analytics solutions, building trust and guiding them through technical and strategic decisions   * Work closely with cross-functional teams (engineering, product, business)   * Help shape opportunities where conversational analytics and AI can drive value  REQUIRED SKILLS * Strong experience as a Data Engineer / Tech Lead within GCP   * Deep expertise in BigQuery and cloud-based data architectures   * Hands-on experience building and integrating ML / AI models into applications   * Experience with LLMs, RAG, embeddings, or agentic AI systems   * Strong programming skills (Python, SQL)   * Experience with API orchestration and system integration   * Familiarity with evaluation pipelines and version control (Git)   * Strong communicator who can bridge technical and business teams   * Curious, pragmatic problem solver with a focus on impact   * Comfortable working in ambiguity and shaping new AI-driven solutions   * Collaborative mindset with the ability to guide and influence others  NICE TO HAVE    * Experience with Gemini, ADK, or similar AI frameworks   * Exposure to CDPs, analytics tooling, or customer data ecosystems  * Experience with MLOps and productionising AI solutions   If you do not meet all the listed qualifications or have gaps in your experience, we still encourage you to apply. At Valtech, we recognize that talent comes in many forms, and we value diverse perspectives and a willingness to learn.  COMMITMENT TO REACHING ALL KINDS OF PEOPLE  We design experiences that work for all kinds of people - and that starts with our own teams. At Valtech, we’re intentional about building an inclusive culture where everyone feels supported to grow, thrive and achieve their goals. No matter your background, you belong here. Explore our Diversity & Inclusion site to see how we’re creating a more equitable Valtech for all.  THE BENEFITS   This is a full time position based in the UK.  Beyond a competitive compensation package, we offer:  * Flexibility, with remote and hybrid work options (country-dependent)  * Career advancement, with international mobility and professional development programs  * Learning and development, with access to cutting-edge tools, training and industry experts  Our benefits are tailored to each location. Your Talent Partner will provide full details during the hiring process.    YOUR APPLICATION PROCESS Once you apply, our Talent Acquisition team will review your application. Your CV should cover key information on relevant experiences and expertise. We do not require information such as age, gender, marital status, or a headshot in your application. We review all candidates based on skills, experience, and potential. ⚠️ Beware of recruitment fraud! We are committed to inclusion and accessibility. If you need reasonable accommodations during the interview process, please either indicate it in your application or let your Talent Partner know.  About Valtech Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.  At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.  At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.  Are you ready to create what’s next? Join us.

Liberis

Some key info for you about Liberis:  🌱 We were founded in 2007 💰 We have provided over $3bn of funding to small businesses so far 🚀 We have been named in CNBC & Statista Top 150 UK Fintechs for 2025 🌍 We're a global team, with a dynamic presence in 6 key locations around the world 🧠 We're a thriving community of over 290 innovative minds 👩🏾 🤝 👨🏼 We're a vibrant melting pot, celebrating over 27 nationalities in our team 🏢 Our team brings experience from over 740 previous companies, from startups to global giants 🎯 We have just been named as one of FinTech’s Finest 50 by Welcome to the Jungle 💪 We’re proud to be an accredited Real Living Wage employer, ensuring everyone is paid fairly for the great work they do!   Our Product & Engineering Team: Liberis is building the embedded finance platform that lets partners around the world offer innovative funding products to their small business customers. We're a growth-stage fintech with teams in London, Nottingham, Atlanta, Stockholm, Munich and Mumbai, and we’re building a global Product, Data & Engineering team that thrives on autonomy, ownership, and is focused on impact! Our teams solve real-world problems for small businesses, shaping products that unlock opportunity at scale.  Engineering is going through an AI-first transformation, rethinking how teams are structured and how they ship. It's changing what a small team can do! We empower our teams to make decisions, move fast, and take full responsibility for the solutions they deliver. You’ll join a team where curiosity is encouraged and collaboration across Product, Data, Delivery and Engineering is the norm.   About our Data & Insights Team: We exist to build the data platforms and analytics that enable every decision at Liberis to be data-informed—and increasingly, to power AI and ML capabilities across the company! We're building composable, reliable data platforms that scale—from ingesting partner transaction data and event streams, to powering analytics dashboards, to feeding ML models with real-time features. We're also supporting the AI/ML platform team with reliable, low-latency feature pipelines and model serving infrastructure. We're collaborative, pragmatic, and we value moving fast by fixing the right problems—not over-engineering, but building to last!   The team is made up of three functions: Data Platform Engineering: Building and scaling ELT pipelines, managing data infrastructure on GCP, and creating the foundation for analytics and ML feature stores. You'll be part of a small, high-performing team of platform engineers focused on reliability, scale, and developer velocity. Analytics Engineering: Transform raw data into trusted models using DBT and SQL, powering self-serve analytics and business intelligence for stakeholders across the company. Data & Business Intelligence: Build dashboards, partner-facing reports, and insights that drive business decisions and revenue outcomes.   What you'll get to do in the role: * Design, build, and maintain resilient data pipelines that ingest data from Azure SQL, SaaS platforms, and event streams into BigQuery. * Write Python code using DLT to define declarative, testable, version-controlled pipelines - no low-code tools, real engineering. * Build and operate ML feature pipelines - low-latency, real-time data streams that feed ML models with accurate, fresh features. * Own the operational health of systems you build - monitoring, alerting, error handling, and incident response. When the data pipeline goes down, merchant credit decisions and ML model predictions suffer. * Collaborate with analytics engineers to understand data needs, validate schema design, and establish data quality standards that both analytics and ML rely on. * Partner with the AI/ML platform team to design feature stores, streaming feature infrastructure, and model serving pipelines that power Liberis' decisioning engine. * Identify and execute optimisation work - improving performance, reliability, and developer velocity without rearchitecting stable systems. * Mentor junior engineers, helping them grow as engineers and supporting their career development. * Participate in technical decisions about platform direction - infrastructure choices, tooling, architecture trade-offs. * Work cross-functionally with product teams, analytics engineers, BI specialists, and the ML platform team to shape data requirements and platform capabilities.   What we think you'll need: * Proven experience within data engineering roles -building and operating data pipelines at scale * Hands-on experience building Modern Data Stack architectures - you understand the layers: ingestion, warehouse, transformation, orchestration, reverse ETL. You've worked with tools like DLT/Fivetran/Airbyte (ingestion), BigQuery/Snowflake/Redshift (warehouse), DBT (transformation), Airflow/similar (orchestration). * Strong Python programming - you write clean, testable, maintainable code with solid error handling and logging. * Fluent SQL - you can write complex queries, understand execution plans, and optimize for performance and cost. * Experience with cloud data platforms - you've built data warehouses in BigQuery, Redshift, Snowflake, or similar; you understand distributed processing, partitioning, cost optimization, and data governance. * Experience with infrastructure-as-code tools (Terraform, CloudFormation, Pulumi) or equivalent - you version control infrastructure and deploy it via CI/CD pipelines. * Experience working in fast-moving environments where requirements evolve and you adapt quickly without losing sight of reliability. * Understanding of DevOps principles - you think in terms of observability, resilience, incident response, and operational excellence. You can set up monitoring and alerting that actually matters.   Bonus points if you have:  * Experience with DLT or similar declarative ELT frameworks; experience with Google Cloud Platform ecosystem (BigQuery, Cloud Run, Pub/Sub, Dataflow); experience with Kafka, Pub/Sub, or event streaming platforms; experience scaling data systems from 0 to 100M+ events/day; experience implementing data quality frameworks (Great Expectations, dbt tests, custom monitoring); background in fintech or high-stakes data reliability environments where data quality directly impacts revenue. * Experience working with distributed, asynchronous teams across timezones; experience in India tech ecosystem or building in resource-constrained environments; experience migrating from legacy data infrastructure (Azure ADF, traditional ETL) to modern cloud-native stacks.   Career development is really important to us here at Liberis, with progression opportunities for both individual contributors and people managers. You can have a look through our Engineering Career Framework via this link  Our hybrid approach Working together in person helps us move faster, collaborate better, and build a great Liberis culture. Our hybrid working policy requires team members to be in the office at least 3 days a week. At Liberis, we embrace flexibility as a core part of our culture, while also valuing the importance of the time our teams spend together in the office. #LI-FC1