Senior Data Engineer
Job Description
Join Cushman & Wakefield, a global leader in real estate services with over 100 years of history and 52,000 employees across 60 countries. As a Senior Data Engineer, you'll play a crucial role in designing and delivering reliable, efficient, and scalable data solutions. This position combines technical expertise with business impact, focusing on building and optimizing data pipelines for transactional, geospatial, and client data.
The role requires a strong background in data engineering, with at least 4 years of experience and proficiency in technologies like SQL, Python, and PySpark. You'll work with modern tools including Azure, Microsoft Fabric, and Databricks, while collaborating with cross-functional teams to deliver custom cloud data solutions.
Your responsibilities will span from analyzing and modeling complex datasets to designing ETL solutions and ensuring data quality. The position offers the opportunity to work in a hybrid environment in Lisbon, Portugal, combining the flexibility of remote work with in-person collaboration.
Cushman & Wakefield, generating $9.5 billion in revenue from core services in 2023, offers a dynamic environment where you can grow your career while working on challenging data engineering projects. You'll be part of a team that values technical excellence, innovation, and the ability to turn data into business value.
This role is perfect for someone who combines technical expertise with business acumen, enjoys working with large-scale data systems, and wants to contribute to a leading global real estate services firm. The position offers the chance to work with diverse datasets, including geospatial data, while implementing best practices in data governance and observability.
Responsibilities For Senior Data Engineer
- Analyze, organize, and model complex datasets in preparation for data lineage and ingestion
- Design robust ETL solutions tailored to business needs and current technology trends
- Build, implement, and optimize data pipelines for transactional, geospatial, and client data
- Monitor and report on data quality, proposing improvements where needed
- Work closely with stakeholders across the business to deliver custom cloud data solutions
- Translate business requirements into effective ETL designs
- Build and maintain stable, automated data ingestion pipelines
- Create data marts to ensure accessible, well-structured data for various use cases
Requirements For Senior Data Engineer
- Minimum 4 years of experience in data engineering or data analysis
- Academic-level education and relevant work experience
- Excellent command of English, both written and spoken
- Proficiency in SQL, Python, and PySpark
- Hands-on experience with Azure, Microsoft Fabric, and Databricks
- Ability to work effectively in cross-functional teams
- Familiarity with Data Management practices, including Data Governance and Data Observability
- Experience with big geospatial data (preferred)
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