remote
Data Engineer - Cushman & Wakefield
Data Engineer
Data Engineer responsible for building and maintaining scalable data pipelines, automating forecasting model workflows, and ensuring data integrity for commercial real estate analytics across the Americas.
About the role
Key Responsibilities
- Design, develop, and maintain robust ETL pipelines to ingest, transform, and store large volumes of commercial real estate data.
- Automate forecasting model workflows using orchestration tools such as Apache Airflow.
- Collaborate with senior economists and analytics leads to translate business requirements into scalable data solutions.
- Implement and optimize data storage solutions on Snowflake and manage cloud resources in AWS.
- Monitor pipeline performance, troubleshoot issues, and ensure data quality and integrity.
- Document data models, processes, and best practices to support reproducibility and knowledge sharing.
Requirements
- 3+ years of experience in data engineering, preferably in real‑estate or financial services.
- Proficiency in Python and SQL for data manipulation and scripting.
- Hands‑on experience with workflow orchestration tools (e.g., Airflow) and cloud platforms (AWS).
- Strong knowledge of modern data warehousing solutions, especially Snowflake.
- Demonstrated ability to design scalable data models and implement reliable ETL processes.
Skills
pythonsqlairflowsnowflakeaws