Analytics Engineer

Monica Vinader

HybridPosted July 26, 2026

About the role

Monica Vinader is seeking an Analytics Engineer to join the Data & AI Platform in London, United Kingdom (hybrid). This is an engineering role at heart; you will own the craft and standards of a well-governed data and AI platform—the models, the ingestion, the semantic layer, and the engineering discipline that keeps definitions and data aligned so every query, whether asked by a person or an AI agent, yields consistent answers.

Analytics Engineer

Monica Vinader

HybridPosted July 26, 2026

About the role

Monica Vinader is seeking an Analytics Engineer to join the Data & AI Platform in London, United Kingdom (hybrid). This is an engineering role at heart; you will own the craft and standards of a well-governed data and AI platform—the models, the ingestion, the semantic layer, and the engineering discipline that keeps definitions and data aligned so every query, whether asked by a person or an AI agent, yields consistent answers.

What you’ll do: - Data modelling & transformation: Build, maintain and optimise data transformation models in dbt on BigQuery; ensure clean, reusable and well-documented structures. Keep business logic in the modelling layer. - Ingestion & the data platform: Set up and maintain data ingestion from third-party sources using automated connectors and Python, own warehouse on GCP/BigQuery with cost management, query performance, and deployment strategies. - Semantic layer & metric governance: Run the semantic layer as a product, maintain single versioned metric definitions, and ensure traceability to sources. - DataOps, quality & governance: Apply software engineering discipline to data; PRs, tests, documentation; monitor data quality and build regression suites; secure data handling with GDPR-aligned governance. - Working with AI & continuous improvement: Use AI tooling in daily work; prototype new data delivery methods to the business; collaborate with the team to ensure the platform enables others to answer business questions.

What you’ll bring: - Strong SQL and experience building data transformation models (dbt); GCP/BigQuery experience; cost/per

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What you’ll do: - Data modelling & transformation: Build, maintain and optimise data transformation models in dbt on BigQuery; ensure clean, reusable and well-documented structures. Keep business logic in the modelling layer. - Ingestion & the data platform: Set up and maintain data ingestion from third-party sources using automated connectors and Python, own warehouse on GCP/BigQuery with cost management, query performance, and deployment strategies. - Semantic layer & metric governance: Run the semantic layer as a product, maintain single versioned metric definitions, and ensure traceability to sources. - DataOps, quality & governance: Apply software engineering discipline to data; PRs, tests, documentation; monitor data quality and build regression suites; secure data handling with GDPR-aligned governance. - Working with AI & continuous improvement: Use AI tooling in daily work; prototype new data delivery methods to the business; collaborate with the team to ensure the platform enables others to answer business questions.