Job Title
Senior Data Engineer
Job Description Summary
Senior Data Engineer | Databricks | Agentic AI | EMEA & APAC
We are the team leading the data transformation of our EMEA and APAC business, and we are hiring a Senior Data Engineer to help build what comes next.
Our Databricks-native Lakehouse is established and mature and already supports the business end to end. The work ahead is more ambitious: applying agentic capabilities at genuine enterprise scale, across a breadth of domains, and shaping how we win in the age of AI.
Job Description
Role: Senior Data Engineer
Senior Data Engineer | Databricks | Agentic AI | EMEA & APAC
We are the team leading the data transformation of our EMEA and APAC business, and we are hiring a Senior Data Engineer to help build what comes next.
Our Databricks-native Lakehouse is established and mature and already supports the business end to end. The work ahead is more ambitious: applying agentic capabilities at genuine enterprise scale, across a breadth of domains, and shaping how we win in the age of AI.
This is a hands-on senior role on key transformation projects across EMEA and APAC. 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.
You will take on problems without a documented precedent, make architectural decisions of real consequence, and build depth across multiple domains early enough to influence where the platform goes next. Very few organisations in our sector have started this work, so the skill set you build here is not one you could assemble elsewhere in this industry.
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.
Building data solutions for domains like custom MDM, geocoding, client mastering, and profiling. Real estate context is a plus but not required.
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.
Core technical skills
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.
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).
A degree in a quantitatively rigorous field such as computer science, data science, econometrics, mathematics, or physics.
Experience with agentic data engineering, using coding agents in real delivery and building the harness around them: repo conventions, reusable context, tests and guardrails that make agent output trustworthy.
A solid technical foundation. The architecture, standards, and best practices are already in place. You build on top, not from scratch.
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.
INCO: “Cushman & Wakefield”
