Data Engineer with Snowflake

About the Role

The Real Estate industry is undergoing an exciting transformation driven by data and technology. Data and insights are at the heart of this mission, powering innovative solutions and delivering exceptional value to clients. Our Enterprise Data Platform combines Master Data Management and Data Governance concepts, built on a modern technology stack, to enable a fully data-driven organization. By breaking down silos and unlocking access to data across regions, we are building core platform capabilities that drive true innovation.

Key Responsibilities

• Analyse and interpret data from multiple source systems to support integration and reporting needs.
• Collaborate with team leads to identify and prioritize business and information requirements.
• Prepare detailed ETL/ELT mapping specifications and develop robust pipelines.
• Write complex SQL and Python scripts for ETL processes.
• Troubleshoot data issues, propose and implement solutions.
• Support the creation of technical documentation.
• Design, implement, and maintain systems using Agile methodologies (Scrum/Kanban).

Requirements

• 3+ years of experience in data platforms/warehousing/lakes: source integration, pipeline development, and analytics.
• Strong experience with Python (e.g. pandas) for scripting and data processing.
• Excellent SQL skills, preferably Postgres and SQL Server (T-SQL).
• Familiarity with AWS services (S3, EC2, Glue).
• Experience with iPaaS tools (SnapLogic preferred, or Jitterbit, Mulesoft, Informatica).
• Hands-on experience with Snowflake, including stages, integrations, formats, procedures, and role-based access management.
• Understanding of scaling, cloning, search optimization, clustering, and query tuning.
• Basic familiarity with BASH scripting and Azure DevOps (Boards, Pipelines, Repos).
• Strong analytical skills with attention to detail and accuracy.
• Ability to communicate effectively with both technical and non-technical stakeholders.
• Solid understanding of data architecture and data modelling best practices.

Nice to Have

• Experience with Master Data Management and Data Governance (profiling, quality, stewardship).
• Knowledge of Elasticsearch.
• Experience with Spatial/GIS database platforms.
• Familiarity with the Commercial Real Estate industry.