At a Glance
- Tasks: Lead the shift to AI orchestration in data engineering and design innovative data solutions.
- Company: Join a global leader in real estate services with a focus on innovation.
- Benefits: Enjoy autonomy, dedicated learning time, and a strong promotion-from-within culture.
- Other info: Embrace diversity and inclusion in a flexible, supportive work environment.
- Why this job: Make a real impact in a dynamic team pushing the boundaries of technology.
- Qualifications: 6+ years in data engineering, strong SQL, Python skills, and a degree in a quantitative field.
The predicted salary is between 60000 - 80000 £ per year.
About the team
We are a Centre of Excellence within a larger EMEA team, with deep specialization in data engineering. Our mission is to build the platform that defines how our organization wins in the age of AI, the solution that will be used globally. We are in the middle of a transition: from a team that writes code to a team that orchestrates AI to write, test, and operate code on our behalf.
About the role
You will help us build that future. This is a hands-on senior engineering role with significant influence on the technical direction of the platform. You will work directly with the team lead and a group of analytical engineers who push each other to stay at the frontier of what is possible.
What you will work on
- Driving the shift from a code writing team to an AI orchestration team. This means building agentic workflows that handle data engineering tasks and CI/CD, designing semantic models for downstream consumption, and implementing an AI Gateway for governance.
- Stewarding our AI amplified Databricks based framework, maintaining it and improving it incrementally as we learn.
- Designing data models that bring sources from anywhere in the world into a single coherent shape.
- Building data solutions for domains like custom MDM, geocoding, client mastering, and profiling. Real estate context is a plus but not required.
- Designing and implementing stable, automated ingestion pipelines from diverse sources.
- Owning production troubleshooting and root cause analysis. When things go wrong, you diagnose and resolve pipeline failures, performance issues, and data quality problems by working through code, logs, and documentation systematically.
- Reporting on data quality and shipping the improvements that move the numbers.
What we are looking for
Core technical skills- Systems thinking. You see the bigger picture and build for scale rather than for the ticket in front of you.
- Production troubleshooting and root cause analysis. You diagnose and resolve pipeline failures, performance issues, and data quality problems under pressure, working through code, logs, and documentation systematically rather than guessing.
- Data modeling. You design cross functional data products, establish data contracts, and handle complex business rules.
- Advanced SQL, including window functions, query optimization, and MERGE/UPSERT operations.
- Python and PySpark. You write reusable, parameterized functions and work comfortably with JSON, CSV, and Parquet.
- Deep experience with Databricks (Declarative Pipelines, DABS, Delta Lake, Spark optimization, job orchestration).
- Familiarity with the Azure ecosystem.
- Working understanding of Unity Catalog.
About you
- Around 6 or more years of relevant experience.
- A degree in a quantitatively rigorous field such as computer science, data science, econometrics, mathematics, or physics.
- Driven and curious. You want to work on things that have not been figured out yet.
- Strong written communication. Async updates and clear documentation are part of the job.
- Advanced Spark optimization (broadcast joins, salting, partitioning strategies).
- Geospatial data processing (H3 indexes, spatial SQL, point in polygon at scale).
- Recursive CTEs and complex SQL patterns.
- Infrastructure familiarity (Azure Portal, resource management, CLI).
- Strong Git workflows and code review habits.
- Real estate domain experience.
What we offer
- Autonomy. We set the high level roadmap. You decide how to get there.
- Dedicated learning time and a team that levels each other up. The frontier moves weekly. We give you the time to keep up with it, and you will be surrounded by people doing the same.
- A growth path. The team is growing and its role in how the company operates is growing with it. There is real room to expand your scope.
- A solid technical foundation. The architecture, standards, and best practices are already in place. You build on top, not from scratch.
Why join Cushman & Wakefield?
As one of the leading global real estate services firms transforming the way people work, shop and live, working at Cushman & Wakefield means you will benefit from being part of a growing global company; career development and a promote from within culture; an organization committed to Diversity and Inclusion.
We're committed to providing work-life balance for our people in an inclusive, rewarding environment. We achieve this by providing a flexible and agile work environment by focusing on technology and autonomy to help our people achieve their career ambitions. We focus on career progression and foster a promotion from within culture, leveraging global opportunities to ensure we retain our top talent. We encourage continuous learning and development opportunities to develop personal, professional and technical capabilities, and we reward with a comprehensive employee benefits program.
We have a vision of the future, where people simply belong. That's why we support and celebrate inclusive causes, not just on days of recognition throughout the year, but every day. We embrace diversity across race, color, religion, sex, national origin, sexual orientation, gender identity or persons with disabilities or protected veteran status. We ensure DEI is part of our DNA as a global community - it means we go way beyond just talking about it - we live it. If you want to live it too, join us.
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.
Senior Data Engineer EMEA in London employer: Cushman & Wakefield
Cushman & Wakefield is an excellent employer for aspiring Analytics Engineers, offering a dynamic work culture in the vibrant setting of Greater London. With a strong emphasis on employee growth, you will benefit from hands-on experience, training, and mentorship while contributing to impactful BI projects. Join a collaborative team that values innovation and supports your journey in developing essential data engineering skills.
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We think this is how you could land Senior Data Engineer EMEA in London
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We think you need these skills to ace Senior Data Engineer EMEA in London
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.