Data Engineer
About the role
This role supports the development, optimization, and maintenance of Cushman & Wakefield’s commercial real estate (CRE) forecasting infrastructure across the Americas. It involves engineering robust data pipelines, automating model workflows, and ensuring the integrity and scalability of forecasting systems.
Responsibilities
Prototype, build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in forecasting models.
Ensure data integrity and consistency across all QIG’s inputs and outputs through rigorous validation and quality control procedures.
Design and enforce structured data interfaces and integration patterns to ensure consistent ingestion and interoperability across internal and external data sources.
Work closely with cross-functional partners to define, refine, and validate data quality rules, using both automated checks and hands-on analysis to ensure outputs meet analytical expectations.
Perform exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and identify anomalies or inconsistencies.
Partner with PRI (Property Research & Intelligence), TDS (Technology Data Solutions), GIS (Geographic Information System) and forecasting team to ensure governance of time series data, as revisions to geography-based competitive sets can occur.
Collaborate with PRI, TDS/GIS and other QIG teams to integrate internal and external data sources into infrastructure deployed by QIG teams.
Ensure Global Think Tank, Americas Research and other stakeholders have access to relevant time series (and forecast) data via various tools and capabilities in coordination with QIG leads.
Work iteratively with partners to refine data outputs, validate usability, and adjust underlying pipelines or transformations as needed to meet evolving analytical requirements.
Requirements
Bachelor’s or Master’s degree in Data Engineering, Data Science, Computer Science, Statistics, or a related technical field. Advanced degree a plus.
5-7 years of experience in data engineering or a hybrid analytical/engineering role, preferably in a forecasting or analytics/production environment.
Real estate experience a plus.
Strong proficiency in Python/R, SQL, Databricks, Delta Lake and data pipeline frameworks (e.g., medallion architecture).
Experience with time series data, econometric / data science modeling workflows, and automation tools.
Familiarity with cloud platforms (e.g., Azure, AWS) and version control systems.
Demonstrated ability to operate in a collaborative, cross-functional environment, contributing both independently and alongside engineering and analytical teams to deliver data solutions.
Comfort working in iterative development settings, balancing hands-on execution with stakeholder collaboration and continuous feedback.
Strong attention to detail and commitment to data quality.
Excellent documentation, communication, and stakeholder management skills; comfortable operating as the technical translator between analytical domain experts and data engineering teams (when appropriate).
Excellent documentation and communication skills for technical audiences.
Ability to participate meaningfully in engineering discussions.
Exposure to geospatial data concepts and CRE or macroeconomic datasets.
Experience working with agile/scrum delivery models in a data and analytics context.
Qualifications
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate’s experience and qualifications. The company will not pay less than minimum wage for this role.
Skills
Python/R, SQL, Databricks, Delta Lake, data pipeline frameworks (e.g., medallion architecture), time series data, econometric / data science modeling workflows, automation tools, cloud platforms (e.g., Azure, AWS), version control systems, agile/scrum delivery models, geospatial data concepts, CRE or macroeconomic datasets.
Benefits
Cushman & Wakefield provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.