Lead Data Analytics Engineer

Collinson Group; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Collinson Group in London is seeking a Lead Data Analytics Engineer to drive enterprise data modelling and analytics automation, empowering squads to deliver trusted Data Products at scale.

You will translate analytics engineering strategy into technical direction, develop reusable capabilities and adopt modern engineering practices across global teams.

Qualifications

• Hands-on analytics engineering/data engineering with deep expertise in data modelling, Snowflake, dbt and SQL.
• Proven experience building automation, reusable engineering frameworks and scalable analytical architectures.
• Strong technical leadership, influencing multiple teams, solving complex engineering challenges and mentoring senior engineers.
• Experience applying GenAI, LLMs, AI agents or Snowflake Cortex to engineering automation.

Responsibilities

• Lead enterprise analytical data modelling, including domain models and semantic layers.
• Establish reusable modelling patterns and common business entities for Data Products.
• Reduce duplication and improve performance, scalability and maintainability of models.
• Provide technical leadership for cross-domain modelling challenges.
• Lead Analytics Automation to transform development, testing, deployment and monitoring.

Skills

Snowflake

dbt

SQL

Python

Git/CI-CD

Semantic Layers

Data Contracts

Data Quality

Observability

AWS

GenAI/LLMs

Tools

Snowflake Cortex

Airflow

Docker

Job description

and details on how your personal data is processed, please review our .Lead Data Analytics Engineer page is loaded## Lead Data Analytics Engineerremote type: Hybridlocations: Londontime type: Full timeposted on: Posted Todayjob requisition id: JR000343# **Job Description****The Role**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*** 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.* 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.* 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.* 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.* Success measure (Data Modelling): greater reuse and consistency of enterprise models with reduced duplication.* Success measure (Automation): measurable reduction in manual engineering effort and improved delivery velocity.* Success measure (Empowerment): squads increasingly able to independently build and operate trusted Data Products.* Success measure (Engineering Excellence): improved reliability, performance, cost efficiency and overall engineering maturity.* Success measure (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.* Success measure (Innovation): successful delivery and adoption of AI-powered engineering capabilities, automation frameworks, and modern engineering practices that create measurable business value.**Knowledge, Skills and Behaviours**Essential* Key technology areas: Snowflake, DBT, SQL, Python, Git/CI/CD, Semantic Layers, Data Contracts, Data Quality and Observability, Snowflake Cortex, LLMs and AI Agents, AWS.* 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.* An individual contributor mindset: equally comfortable defining strategy and implementing it through working code, prototypes and production-ready solutions.Desirable* Python and modern data observability/lineage experience.* Experience enabling self-service engineering across distributed analytics teams.We want our people to feel recognised, supported and able to thrive both at work and beyond it.We offer a competitive reward package designed to support your financial, physical and mental wellbeing, alongside opportunities to learn, develop and be recognised for the contribution you make. Benefits vary by role and location, and full details will be shared as part of the application process.# **Equal opportunities: Our commitment to inclusion**Collinson Group is an equal opportunities employer. We welcome applications from people of all backgrounds, identities and experiences, and believe that different perspectives make our business stronger.Collinson Group is powered by a culture of innovation, collaboration, and integrity. Our employee experience brings together everything that makes us unique: our strong values, our commitment to sustainability, our recognition programmes, and our inclusive culture. Most importantly, it's our people who make the difference. At Collinson Group, we're curious, hardworking, humble, and focused on creating impact together, which is why we're proud to be recognised as a top workplace.**Better journeys start here - including your own.**Join a growing global business where you can solve meaningful challenges, collaborate with talented people around the world and help shape the future of travel, loyalty and customer experience.Bring your perspective, grow beyond your role and make an impact that reaches beyond profit.**Your next journey could start here**We are always interested in meeting talented people who share our ambition. Join our talent community and tell us more about your experience, interests and aspirations. Our Talent Acquisition team will be in touch when an opportunity matches your skills.**Join our talent community**