Data Engineer

Job Title: Data Engineer Job Description: Supporting the development, optimization, and maintenance of Cushman & Wakefield’s commercial real estate (CRE) forecasting infrastructure across the Americas. This role focuses on engineering robust data pipelines, automating model workflows, and ensuring the integrity and scalability of forecasting systems. Operate as a self‑sufficient data practitioner, capable of independently delivering data solutions or working side‑by‑side with technology teams to ensure alignment and production readiness of QIG capabilities. Time Series Data Engineering, Maintenance & Automation (40%) 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 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, TDS, GIS and forecasting teams 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. Technical Support (40%) Create and maintain documentation of any synthetic data model architecture, data flows, and diagnostic procedures. Have a strong grasp of field‑level data lineage and traceability to support transparency, reproducibility, and downstream analytical confidence. Partner with Head of Data Science & Geospatial Analytics to build state‑of‑the‑art, novel real‑estate datasets, with additional relevant data geospatially integrated (e.g., demographics, socioeconomic data, zoning or flood maps, climate or walk score information); produce detailed specifications that guide engineering implementation. Develop internal documentation and process automation, and serve as an expert on the integration, application and processing of internal data, 3rd‑party vendor data and other public data (e.g., Census TIGER, IPUMS) as appropriate with QIG leads. Advise, integrate and execute normalization methods with internal and external partners, co‑developing approaches with technology teams when necessary and validating outputs through hands‑on implementation and analysis. Identify new data use cases for proprietary data, ensure appropriate cleaning and normalization techniques so data can be used in statistical, econometric and other commercial analytics applications. Infrastructure Enhancement & Collaboration (20%) Contribute to the evolution of the QIG data infrastructure by identifying opportunities for efficiency gains, automation, and scalability. Support the integration of emerging technologies (e.g., ML/AI, advanced lakehouse patterns) into data workflows under guidance from senior team members through hands‑on experimentation, prototyping, or coordination with TDS as needed. Coordinate with TDS and PRI on internal data and technology initiatives; contribute hands‑on development or feedback where appropriate to scale, optimize, and productionize solutions in support of QIG capabilities. Serve as the key liaison for all external data dependencies; monitor the evolution of 3rd‑party data products and capabilities, assess their fit against QIG analytical requirements, and produce intake specifications when new sources are approved for integration. When appropriate, maintain a living requirements register and change log that tracks open data engineering requests, their status in the TDS backlog, acceptance criteria, and QIG sign‑off outcomes. 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. Exposure to geospatial data concepts and CRE or macroeconomic datasets. Experience working with agile/scrum delivery models in a data and analytics context. Compensation and Benefits Compensation range: $114,750.00 – $135,000.00. The position may be covered by collective bargaining agreements and pay will vary by location, experience and other factors. The company will not pay less than minimum wage for this role. Cushman & Wakefield provides eligible employees with a comprehensive benefits package that generally includes 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. Equal Opportunity Employment Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated. In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at View phone number on click.appcast.io or email View email address on click.appcast.io. #J-18808-Ljbffr