Lead Data Analytics Engineer

Lead Data Analytics Engineer Apply here Collinson is the global, privately-owned company dedicated to helping the world to travel with ease and confidence. The group offers a unique blend of industry and sector specialists who together provide market-leading airport experiences, loyalty and customer engagement, and insurance solutions for over 400 million consumers. Collinson is the operator of Priority Pass, the world’s original and leading airport experiences programme. Travellers can access a network of 1,500+ lounges and travel experiences, including dining, retail, sleep and spa, in over 650 airports in 148 countries, helping to elevate the journey into something special. We work with the world’s leading payment networks, over 1,400 banks, 90 airlines and 20 hotel groups worldwide. We have been bringing innovation to the market since inception – from launching the first independent global VIP lounge access Programme, Priority Pass to being the first to sell direct travel insurance in the UK through Columbus Direct and creating the first loyalty agency of its kind in the travel sector with ICLP. Today we still invest heavily in innovation to ensure that we continue to deliver superior customer experiences. Key clients include Visa, Mastercard, American Express, Cathay Pacific, British Airways, LATAM, Flying Blue, Accor, EasyJet, HSBC, Chase, HDFC. Our mission is focused on doing good beyond profit, which for us means we seek out opportunities for our people to share in our success and that we give back to the communities and people within which we work. Never short of ambition, the success of our business is delivered through the diverse and talented team of over 1,800 global colleagues. Purpose of the job The Lead Data Analytics Engineer is a senior technical leadership role responsible for advancing Enterprise Data Modelling, Analytics Automation and Engineering Empowerment across Global Analytics. Working directly with the Head of Analytics Engineering, the role translates the Analytics Engineering strategy into technical direction, reusable capabilities and modern engineering practices. The role enables squads to independently deliver trusted, scalable Data Products while maintaining enterprise consistency and engineering excellence. Key Responsibilities: 1. Enterprise Data Modelling • Lead the enterprise approach to analytical data modelling, including domain models, dimensional models and semantic layers. • Establish reusable modelling patterns and common business entities that create consistency across Data Products. • Reduce duplication and improve the performance, scalability and maintainability of analytical models. • Provide technical leadership for complex and cross-domain modelling challenges. 2. Analytics Automation & AI • Lead the Analytics Automation agenda, transforming how analytics is developed, tested, deployed, documented and monitored. • Apply Snowflake Cortex, LLMs, intelligent agents and automation to improve engineering productivity and quality. • Build reusable automation capabilities and accelerators rather than one-off solutions. • Identify and industrialise emerging technologies that materially improve Analytics Engineering. 3. Engineering Empowerment • Create frameworks, tools, templates and reusable components that enable squads to deliver independently and faster. • Improve developer experience and simplify the journey from development to production. • Remove recurring technical bottlenecks through self-service and reusable engineering capabilities. • Enable domain teams to build trusted Data Products within established engineering standards. 4. Technical Leadership & Modernisation • Act as a senior technical authority for Analytics Engineering, providing direction on complex solutions and technical decisions. • Drive engineering standards, modernisation, platform performance and reduction of technical debt. • Mentor engineers and raise technical capability through communities of practice and knowledge sharing. • Partner with the Head of Analytics Engineering to shape the technical roadmap and future engineering capability. Key Technology Areas: Snowflake • DBT • SQL • Python • Git/CI/CD • Semantic Layers • Data Contracts • Data Quality & Observability • Snowflake Cortex • LLMs & AI Agents • AWS Skills & Experience: Must Have • Strong hands-on Analytics Engineering/Data Engineering experience with deep expertise in data modelling, Snowflake, dbt and SQL. • Proven experience building automation, reusable engineering frameworks and scalable analytical architectures. • Strong technical leadership experience, including influencing multiple teams, solving complex engineering challenges and mentoring senior engineers. • Experience applying GenAI, LLMs, AI agents or Snowflake Cortex to engineering automation. • A hands-on, outcome-driven engineering leader who leads from the front by designing, building, and delivering solutions. This role requires an individual contributor mindset, someone who is equally comfortable defining strategy and implementing it through working code, prototypes, and production-ready solutions. Nice to Have • Python and modern data observability/lineage experience. • Experience enabling self-service engineering across distributed analytics teams. Success Measures • Data Modelling: Greater reuse and consistency of enterprise models with reduced duplication. • Automation: Measurable reduction in manual engineering effort and improved delivery velocity. • Empowerment: Squads increasingly able to independently build and operate trusted Data Products. • Engineering Excellence: Improved reliability, performance, cost efficiency and overall engineering maturity. • Technical Leadership: Recognised as the technical lead who drives delivery through hands-on contribution, accelerates engineering outcomes, and enables teams by building reusable capabilities rather than relying solely on governance or oversight. • Innovation: Successful delivery and adoption of AI-powered engineering capabilities, automation frameworks, and modern engineering practices that create measurable business value. Collinson is an equal opportunity employer and welcomes differences in all their forms including: colour, race, ethnicity, gender identity, sexual orientation, neurodivergence, family status, age, individuals with disabilities and people from all backgrounds, cultures and experiences as we strongly believe this contributes to our on-going success. We are focused on continually evolving our purpose driven, high performing culture, providing an environment where our people have the opportunity to achieve their full potential and do interesting and meaningful work. Our company values are: Take Action, Do the right thing, One team and Be insight led. These help guide everything we do internally in terms of how we think, act and interact, right through to how we deliver value to our customers and clients. In your application, please feel free to note which pronouns you use (For example - she/her/hers, he/him/his, they/them/theirs, etc). If you need any extra support throughout the interview process, then please email us at [email protected] Division Technology & Data Role Data and ML Platform Locations London Remote status Hybrid London About Collinson We use our expertise and products to craft customer experiences. Our range of services helps global brand acquire, engage and retain choice-rich customers. © 2023 Collinson International Limited. Registered in England & Wales under registration No. 2577557 Registered address : 3 More London Riverside, London, SE1 2AQ, United Kingdom.