Analytics Engineer: AI-Ready Data on Databricks Platform

cw; Greater London; On-site; GBP 90,000 - 120,000; Full time

Job summary

Cushman & Wakefield is seeking an Analytics Engineer to lead semantic modeling and data platform improvements across EMEA & APAC. You will bridge data engineering with business stakeholders, turning commercial questions into scalable data assets and AI-ready pipelines.

You will design, build, and govern semantic models, datasets, and automated scoring frameworks, enabling executive decision-making and improved transformation outcomes.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Mathematics, Statistics, Econometrics, or related quantitative discipline.
• Minimum 3 years of experience in a data engineering, analytics engineering, or BI development role.
• 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.

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 the design of upstream data assets, ensuring they meet scalable requirements.
• Contribute to data assets and pipelines that support AI, machine learning, and agentic workflows; the default delivery mode.
• Monitor and optimise the performance of data models and semantic layers, addressing data quality before executive decks.
• Support platform adoption through documentation, standards, and knowledge transfer; contribute to best practices for data modelling and dataset architecture.
• Participate in peer reviews of data models to ensure consistency and quality before release into business-critical decks.

Skills

SQL

Data modeling

Data governance

Communication

Analytical thinking

Agile delivery

English fluency

Education

Bachelor's/Master's in quantitative field

Tools

Databricks

Azure Synapse

Snowflake

Power BI

Microsoft Fabric

Databricks Certification

Job description

Cushman & Wakefield is seeking an Analytics Engineer to lead semantic modeling and data platform improvements across EMEA & APAC. You will bridge data engineering with business stakeholders, turning commercial questions into scalable data assets and AI-ready pipelines.

You will design, build, and govern semantic models, datasets, and automated scoring frameworks, enabling executive decision-making and improved transformation outcomes.