Junior Analytics Engineer in Vauxhall

We’re looking for a Junior Analytics Engineer to join the Analytics Engineering pillar of our EMEA Business Intelligence team.

You’ll help build and maintain the data foundation behind BI delivery across EMEA, supporting senior Analytics Engineers on semantic models, curated datasets and reusable data assets on our central data platform. You’ll work closely with the BI and Data Science & Engineering teams, and start to build the business context to turn real needs into well-structured data. As more of our data supports AI and agentic use cases alongside traditional BI, you’ll help lay that groundwork. This is a learning role for someone technically curious. You’ll be guided throughout, with clear routes to take on more responsibility and grow toward a more senior role.

Key responsibilities:

• Build and maintain: contribute to semantic models and curated datasets under the guidance of senior engineers.
• Standardise: help make datasets, business logic and data models consistent and reusable across BI teams and markets.
• Onboard market data: assist with bringing market-specific datasets onto the central platform, working with local stakeholders to understand sources and requirements.
• Support BI delivery: work with senior colleagues to make sure data assets meet the needs of BI products from the BI Development team.
• Learn the business: develop an understanding of the context behind data requests and help translate needs into data structures and logic.
• Quality and performance: contribute to data quality checks, basic performance monitoring and testing before release.
• AI-ready foundations: support early-stage work preparing clean, well-structured datasets for future AI and agentic applications.
• Document and review: keep clear documentation, take part in peer reviews, and follow team standards on modelling, naming and governance.
• Develop: take an active part in training, bootcamps and mentoring.

Skills and experience:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Mathematics, Statistics or a related technical field.
• Some practical experience in data engineering, analytics engineering or BI, through a job, internship or academic project.
• Foundational SQL, with a willingness to build proficiency in optimising data models.
• Basic familiarity with data modelling concepts such as star schema or dimensional modelling.
• Exposure to Databricks, Microsoft Fabric, Azure Synapse or Snowflake.
• Awareness of Power BI or other BI tools.
• Curiosity about AI, machine learning and agentic technologies.
• Interest in business needs and developing commercial awareness.
• Strong attention to detail and a methodical approach to building, testing and documenting.
• Good communication skills: asking clear questions and documenting work clearly.
• A collaborative, proactive mindset and eagerness to learn.

Please note: this is a direct search led by Cushman & Wakefield. We only work with recruitment agencies on our preferred supplier list, and only where a signed and in date agreement is in place and the agency has been directly instructed on the role by a member of our Talent Acquisition team. We do not accept speculative or unsolicited CVs submitted to any of our employees or outside of our agreed process. No agency fees will be payable in these circumstances.

Cushman & Wakefield is an equal opportunity / affirmative action employer. All qualified candidates will receive consideration for employment without regard to ethnicity, gender, gender identity or expression, sexual orientation, age, disability, religion, marital status, or any other legally protected characteristic. Cushman & Wakefield is committed to equity in employment, and our goal is to have a diverse, inclusive and barrier-free workplace.

If you are a person with a disability and need any other accessible accommodations during the hiring process, you are invited to bring this to the Talent Acquisition Advisor’s attention once they have made contact.

Location: London, United Kingdom

Type: Full time