{"schemaVersion":"jobsearcher.job.v1","id":"672d4ac45545fdfe45e3ee3d","url":"https://jobsearcher.com/jobs/672d4ac45545fdfe45e3ee3d","canonicalUrl":"https://jobsearcher.com/jobs/672d4ac45545fdfe45e3ee3d","title":"Data Engineer","description":"Job Title\nData Engineer\nJob Description Summary\nKey Objectives:\n\nSupports the development, optimization, and maintenance of Cushman & Wakefield’s commercial real estate (CRE) forecasting infrastructure across the Americas. This role is focused on engineering robust data pipelines, automating model workflows, and ensuring the integrity and scalability of forecasting systems.\n\nOperate 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 on an iterative basis.\n\nWorks closely with senior economists, analytics leads, and technical teams to deliver high-quality, production-ready data solutions that underpin the firm’s House View and related analytical products.\nJob Description\nTime Series Data Engineering, Maintenance & Automation (40%)\nPrototype, build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in forecasting models.\nEnsure 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.\nWork 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.\nPerforms exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and identify anomalies or inconsistencies.\nPartner 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.\nCollaborate with PRI, TDS/GIS and other QIG teams to integrate internal and external data sources into infrastructure deployed by QIG teams.\nEnsure 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.\nTechnical Support (40%)\nCreate and maintain documentation of any synthetic data model architecture, data flows, and diagnostic procedures. Have strong grasp of field-level data lineage and traceability to support transparency, reproducibility, and downstream analytical confidence.\nPartner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real estate dataset, 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.\nDevelop internal documentation and process automation, and serve as 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.\nAdvise, 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.\nIdentify 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.\nInfrastructure Enhancement & Collaboration (20%)\nContribute to evolution of the QIG data infrastructure by identifying opportunities for efficiency gains, automation, and scalability.\nSupport 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.\nCoordinate with TDS and PRI on internal data and technology initiatives; contributing hands-on development or feedback where appropriate to scale, optimize, and productionize solutions in support of QIG capabilities.\nServe 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. As needed, partner with technology teams to evaluate and integrate internally managed data sources.\nWhen/where 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.\nRequirements:\nBachelor’s or Master’s degree in Data Engineering, Data Science, Computer Science, Statistics, or a related technical field. Advanced degree a plus.\n5-7 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.\nStrong proficiency in Python/R, SQL, Databricks, Delta Lake and data pipeline frameworks (e.g., medallion architecture).\nExperience with time series data, econometric / data science modeling workflows, and automation tools.\nFamiliarity with cloud platforms (e.g., Azure, AWS) and version control systems.\nDemonstrated ability to operate in a collaborative, cross-functional environment, contributing both independently and alongside engineering and analytical teams to deliver data solutions.\nComfort working in iterative development settings, balancing hands-on execution with stakeholder collaboration and continuous feedback.\nStrong attention to detail and commitment to data quality.\nExcellent documentation, communication, and stakeholder management skills; comfortable operating as the technical translator between analytical domain experts and data engineering teams (when appropriate).\nExcellent documentation and communication skills for technical audiences. Ability to participate meaningfully in engineering discussions.\nExposure to geospatial data concepts and CRE or macroeconomic datasets.\nExperience working with agile/scrum delivery models in a data and analytics context.\n\nCushman & Wakefield also 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.\n\nThe 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.\n\nThe company will not pay less than minimum wage for this role.\n\nThe compensation for the position is: $ 114,750.00 - $135,000.00\nCushman & 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.\nIn 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 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.\nINCO: “Cushman & Wakefield”","company":"Cushman & Wakefield","rawCompany":"cushman wakefield","city":"Costa Mesa","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-08-04T23:27:38.003Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"17-2199.00","title":"Engineers, All Other","slug":"engineers-all-other"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"531390","title":"Other Activities Related to Real Estate","slug":"other-activities-related-to-real-estate"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Data Engineer","description":"Job Title\nData Engineer\nJob Description Summary\nKey Objectives:\n\nSupports the development, optimization, and maintenance of Cushman & Wakefield’s commercial real estate (CRE) forecasting infrastructure across the Americas. This role is focused on engineering robust data pipelines, automating model workflows, and ensuring the integrity and scalability of forecasting systems.\n\nOperate 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 on an iterative basis.\n\nWorks closely with senior economists, analytics leads, and technical teams to deliver high-quality, production-ready data solutions that underpin the firm’s House View and related analytical products.\nJob Description\nTime Series Data Engineering, Maintenance & Automation (40%)\nPrototype, build and maintain automated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in forecasting models.\nEnsure 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.\nWork 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.\nPerforms exploratory data analysis and profiling on raw and processed datasets to validate pipeline outputs and identify anomalies or inconsistencies.\nPartner 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.\nCollaborate with PRI, TDS/GIS and other QIG teams to integrate internal and external data sources into infrastructure deployed by QIG teams.\nEnsure 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.\nTechnical Support (40%)\nCreate and maintain documentation of any synthetic data model architecture, data flows, and diagnostic procedures. Have strong grasp of field-level data lineage and traceability to support transparency, reproducibility, and downstream analytical confidence.\nPartner with Head of Data Science & Geospatial Analytics to build state-of-the-art, novel real estate dataset, 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.\nDevelop internal documentation and process automation, and serve as 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.\nAdvise, 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.\nIdentify 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.\nInfrastructure Enhancement & Collaboration (20%)\nContribute to evolution of the QIG data infrastructure by identifying opportunities for efficiency gains, automation, and scalability.\nSupport 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.\nCoordinate with TDS and PRI on internal data and technology initiatives; contributing hands-on development or feedback where appropriate to scale, optimize, and productionize solutions in support of QIG capabilities.\nServe 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. As needed, partner with technology teams to evaluate and integrate internally managed data sources.\nWhen/where 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.\nRequirements:\nBachelor’s or Master’s degree in Data Engineering, Data Science, Computer Science, Statistics, or a related technical field. Advanced degree a plus.\n5-7 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.\nStrong proficiency in Python/R, SQL, Databricks, Delta Lake and data pipeline frameworks (e.g., medallion architecture).\nExperience with time series data, econometric / data science modeling workflows, and automation tools.\nFamiliarity with cloud platforms (e.g., Azure, AWS) and version control systems.\nDemonstrated ability to operate in a collaborative, cross-functional environment, contributing both independently and alongside engineering and analytical teams to deliver data solutions.\nComfort working in iterative development settings, balancing hands-on execution with stakeholder collaboration and continuous feedback.\nStrong attention to detail and commitment to data quality.\nExcellent documentation, communication, and stakeholder management skills; comfortable operating as the technical translator between analytical domain experts and data engineering teams (when appropriate).\nExcellent documentation and communication skills for technical audiences. Ability to participate meaningfully in engineering discussions.\nExposure to geospatial data concepts and CRE or macroeconomic datasets.\nExperience working with agile/scrum delivery models in a data and analytics context.\n\nCushman & Wakefield also 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.\n\nThe 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.\n\nThe company will not pay less than minimum wage for this role.\n\nThe compensation for the position is: $ 114,750.00 - $135,000.00\nCushman & 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.\nIn 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 1-888-365-5406 or email Accommodations@cushwake.com. Please refer to the job title and job location when you contact us.\nINCO: “Cushman & Wakefield”","datePosted":"2026-08-04T23:27:38.003Z","dateModified":"2026-08-04T23:27:38.003Z","hiringOrganization":{"@type":"Organization","name":"Cushman & Wakefield","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Costa Mesa","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"672d4ac45545fdfe45e3ee3d"},"url":"https://jobsearcher.com/jobs/672d4ac45545fdfe45e3ee3d"}}