Analytics Engineer – Semantic Modeling for AI-Ready Data

Cushman & Wakefield; City of Westminster; On-site; GBP 60,000 - 90,000; Full time

Job summary

Cushman & Wakefield seeks an Analytics Engineer to join the Data & Analytics team across EMEA and APAC. You will design semantic models, curate datasets, and bridge data engineering with business stakeholders to drive enterprise-scale analytics and AI-readiness.

You will build scalable data assets on Databricks, leverage SQL and Power BI, and contribute to governance, documentation, and robust data pipelines. Strong communication and problem-solving are essential.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, Econometrics, or a related quantitative discipline.
• Minimum 3 years of experience in data engineering, analytics engineering, or BI development.
• Strong hands-on experience with Databricks or an equivalent enterprise data platform (Azure Synapse, Microsoft Fabric, Snowflake).
• Proficiency in SQL and experience building and optimising semantic or data models at scale, including window functions and complex business logic.
• Solid understanding of data modelling principles - star schema, dimensional modelling, DAX.
• Experience with Power BI and the Microsoft Power Platform, including building on top of central/curated data models.
• Familiarity with data pipeline concepts, transformation logic, and ETL/ELT processes.
• Working understanding of how data assets are structured to support AI, ML, and agentic use cases.
• Comfortable translating business logic into structured, auditable transformations.
• Strong understanding of data governance, data quality, and documentation best practices.

Responsibilities

• Design, build, and maintain semantic models and curated datasets on the Databricks platform, ensuring they are performant, reusable, and aligned with governance standards.
• Act as the technical bridge between the central Data Engineering team and transformation/business stakeholders, translating ambiguous business questions into structured data models.
• Build and maintain automation/AI-readiness scoring frameworks - turning taxonomy and process data into structured, defensible metrics used in executive business cases.
• Produce the quantitative backbone of transformation business cases: current-state baselines, savings and benefit tracking, scenario/what-if models, and before/after comparisons.
• Standardise datasets and business logic so that transformation workstreams build consistently on a shared foundation.
• Collaborate with the data engineering team on upstream data assets, ensuring scalability and relevance for analytics.
• Contribute to data assets and pipelines structured to support AI, ML, and agentic workflows.
• Monitor and optimise the performance of data models and semantic layers, addressing data quality issues before executive reporting.
• Support platform adoption through documentation, standards, and knowledge transfer, including data modelling conventions and dataset architecture.
• Participate in peer reviews of data models to ensure consistency and quality before release into business-critical decks.

Skills

SQL

Data modelling

Power BI

Stakeholder communication

Ambiguity handling

Education

Quantitative degree

Tools

Databricks

Azure Synapse

Snowflake

Microsoft Fabric

Power Platform

Job description

Cushman & Wakefield seeks an Analytics Engineer to join the Data & Analytics team across EMEA and APAC. You will design semantic models, curate datasets, and bridge data engineering with business stakeholders to drive enterprise-scale analytics and AI-readiness.

You will build scalable data assets on Databricks, leverage SQL and Power BI, and contribute to governance, documentation, and robust data pipelines. Strong communication and problem-solving are essential.