About the Company You'll be joining a global leader in real estate services and technology solutions. Known for combining deep market expertise with cutting-edge innovation, this business is committed to modernising how property and investment decisions are made. You'll be part of a collaborative, forward-thinking environment that values creativity, accountability, and growth-where your contributions will directly shape the future of real estate technology. Role Responsibilities Architect, build, and optimise scalable ETL pipelines for diverse datasets. Onboard, document, and curate external datasets for internal use. Perform data validation, forensic analysis, and troubleshooting. Deliver high-quality, maintainable Python code and participate in peer reviews. Collaborate with stakeholders and researchers to support analytics and product development. Integrate data from APIs, S3 buckets, and structured/unstructured sources (JSON, CSV, Excel, PDF, Parquet). Join geospatial datasets with external data sources and apply complex transformations. Define validated data schemas and create clear documentation for partners and teams. Explore and evaluate new data engineering tools and technologies. Role Requirements 5 years' experience in data engineering, analytics, or related roles. Strong proficiency in Python, with demonstrated experience on large-scale projects. Solid understanding of algorithms, data structures, and relational databases. Experience with test-driven development and Git version control. Portfolio of past work (GitHub contributions, open-source, blogs, or demos). Knowledge of data cleansing, validation, and basic statistics. Background in working with Agile methods and fast iteration cycles. Bachelor's degree in Computer Science, Data Engineering, or related field (or equivalent experience).