Analytics Engineering Lead

Join a leading consumer organisation in London as an Analytics Engineering Lead, shaping how trusted data is modelled, governed and consumed across key business domains.

You’ll combine deep technical expertise with strong stakeholder partnering to deliver scalable data products that enable faster, smarter decision-making.

The Role

• Lead analytics engineering at a business-domain level (e.g., Customer, Commercial, Operations), setting direction and driving delivery with a high degree of autonomy
• Act as a hands-on technical leader for data modelling, testing, documentation and governance best practices
• Build strong partnerships across Product, Marketing, Finance, Engineering and Data to define requirements and deliver high-impact solutions
• Mentor analytics engineers through code reviews, pairing and knowledge sharing (no formal line management responsibilities stated)

What You’ll Do

• Plan and deliver domain-level analytics engineering initiatives aligned to strategic priorities
• Design, build and evolve reusable data models and transformation pipelines using dbt and Snowflake
• Own end-to-end delivery of datasets and models, coordinating input from other engineers where needed
• Make architectural and technical decisions balancing performance, scalability, cost and usability
• Embed high standards of data quality through testing, monitoring and governance practices
• Use metrics (e.g., data quality, pipeline performance, adoption) to drive continuous improvement
• Identify and implement opportunities to improve processes, tooling and workflows
• Represent analytics engineering in cross-team discussions, negotiating priorities and trade-offs

What We’re Looking For

• Advanced SQL skills (complex transformations, modelling and performance optimisation)
• Extensive hands-on dbt experience building scalable, maintainable analytics models
• Strong data modelling & architecture experience across complex business domains (minimum 7 years in analytics engineering/data modelling)
• Strong Snowflake experience, including performance optimisation and cost-efficient warehouse design (experience with other cloud data platforms beneficial)
• Proven ability to lead and evolve analytics engineering solutions at a domain level
• Python skills for automation and data processing
• Proficiency with git and collaborative development workflows
• Confident stakeholder management: able to influence and partner effectively at multiple levels
• Comfortable operating with ownership and autonomy in ambiguous problem spaces
• Experience mentoring and developing other engineers
• Experience working in agile delivery environments, focused on outcomes and continuous improvement
• Strong technical curiosity and desire to stay current with modern data practices

Nice to Have

• Data monitoring/observability tooling (e.g., DataDog)
• Orchestration and ingestion tooling (e.g., Dagster, Fivetran)
• Data visualisation familiarity (e.g., Tableau)
• Exposure to AWS services and infrastructure-as-code (e.g., Terraform)
• Familiarity with analytics tooling such as GA4, GTM, BigQuery

Package

• Permanent role, 40 hours per week
• Location: London, United Kingdom (on-site requirement)
• Salary: Not provided
• Tech environment includes: Snowflake, dbt, SQL, Python, Fivetran, Dagster, DataDog, Tableau, AWS, Terraform, GitHub, Jira, Confluence (you don’t need experience with everything listed)

Process / How to Apply
Apply via the job board/careers page with your CV. If your experience aligns with what we’re looking for, we’ll be in touch to outline the next steps in the process.