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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).
