Analytics Engineering Manager

We use our expertise and products to craft customer experiences which enable some of the world’s best known brands to acquire, engage and retain the most demanding and choice-rich customers. In particular, our unique expertise and insight into high earning, frequent travellers allows us to create products and solutions for our clients that inspire greater customer engagement to drive more profitable relationships, enrich their travel experiences, protect what matters and assist in in times of need.

While specialising in Financial Services, Travel and Retail, we also support clients in multiple sectors. We have worked with over 90 airlines, 20 hotel groups and more than 600 financial institutions and banks, with clients including Accor Hotels, Air France KLM, American Express, British Airways, Cathay Pacific, Diners Club, Mandarin Oriental, Mastercard, Radisson Hotel Group, Sephora, Visa and Vhi.

We take our 30 years’ experience working with these kinds of household names in over 170 countries, and help our clients to deliver the smarter experiences it takes to differentiate their propositions, and help them win deeper devotion with their customers.

Collinson is a privately-owned entrepreneurial business with 2,000 passionate people working in 20 locations worldwide. Our solutions include Priority Pass, the world’s best known airport experiences programme, while we are also the trusted partner behind many of the leading financial services, airline and hotel brand’s reward programmes and loyalty initiatives.

We are seeking an Analytical Engineering Manager to lead the next stage of our analytical data evolution — ensuring that Collinson’s data models, definitions, and analytical layer are scalable, trusted, and business-aligned.

Working closely alongside the Principal Data Engineer, and data engineering manager you will bridge technical foundations and business needs: defining how data is shaped, documented, and served for analytics, AI, and product insight.

You’ll lead a team of analytics engineers focused on modelling excellence, semantic consistency, and governed reuse, ensuring that every analytical dataset reflects a shared understanding of the business.

This role requires a balance of technical credibility, delivery discipline, and coaching mindset — shaping how data is modelled and used across Collinson.

Lead, mentor, and develop an analytical engineering team focused on modelling standards, quality, and reusability.

Partner with the Principal Data Engineer to co-own end-to-end data delivery — from foundational pipelines through to analytical data layers.

Shape career growth, training, and performance pathways that develop deep data craftsmanship within the team.

Foster a culture of collaboration between data engineering, governance, and analytics — aligning priorities through shared objectives.

Define and embed best practices in data modelling, including standards for naming, documentation, and business logic representation.

Lead the design of subject-area models and data contracts that form the foundation for reporting, AI, and personalization.

Champion the evolution toward a semantic and governed analytical layer, ensuring traceability from raw data to business outcomes.

Partner with Product, Analytics, and Technology teams to translate business concepts into consistent, reusable data assets.

Maintain high standards of quality and simplicity in data design — prioritizing clarity, trust, and performance over complexity.

Work hand-in-hand with the Principal Data Engineer to align platform evolution, modelling standards, and delivery governance.

Contribute to the Data & Analytics strategy and roadmap, ensuring analytical engineering practices scale with Collinson’s data ambitions.

Represent analytical engineering in cross-functional forums, advocating for trusted data, lineage, and definition alignment.

Partner with Governance, Data Science, and BI teams to ensure analytical models meet the needs of both operational and strategic insight.

Knowledge, skills and experience required

Proven experience leading data or analytics engineering teams within a modern cloud data platform.

Deep understanding of data modelling principles, including dimensional and domain-driven design.

Experience shaping and governing semantic or analytical layers that underpin enterprise analytics.

Principal Data Engineer).

Excellent communication and stakeholder management across business, data, and technology teams.

A passion for quality, maintainability, and clarity in analytical data design.

Exposure to data contracts, metadata management, or data governance frameworks.

Awareness of analytics enablement in AI-driven or personalization contexts.

Experience working with agile data teams balancing short-term delivery with long-term architecture.

Understanding of how analytical engineering integrates into data product, ML, and self-service strategies.