Data Engineer, Hometree

• Experience: Practical production experience building, optimising and maintaining data pipelines and warehouses, using BigQuery or similar cloud data solutions
• Technical Skills: Strong proficiency in SQL and ETL/ELT frameworks and experience with data modelling, optimisation, and pipeline orchestration. Python or similar programming language is a nice to have!
• Cloud Proficiency: Experience working with cloud platforms such as Google Cloud Platform (GCP) or AWS, particularly with services related to data storage and analytics
• Data Infrastructure: Demonstrated experience in data warehousing concepts, schema design, and optimising large-scale data systems
• Strong problem-solving abilities - Great attention to detail, capable of independently diagnosing complex issues and proactively identifying constructive, scalable solutions
• Effective communicator - Comfortable articulating technical concepts clearly to both technical and non-technical stakeholders, ensuring alignment and clarity across diverse teams
• Self-motivated and collaborative - Able to independently manage and deliver projects while actively engaging in cross-functional collaboration to achieve shared objectives

Desirable

• We're seeking a motivated and detail orientated Data Engineer with experience in building and managing scalable data pipelines and infrastructure
• You'll be responsible for developing robust ETL/ELT processes, optimising and maintaining data warehouse, and ensuring data quality and standards through comprehensive monitoring and governance
• Collaborating closely with our Data, Tech and Product teams, you'll help shape and support our data strategy
• The ideal candidate should have familiarity in SQL and cloud-based data solutions, be driven towards automated solutions and thrives in transforming complex data infrastructure into streamlined, reliable, and actionable assets
• Own Data Infrastructure: Design, develop, and maintain scalable data pipelines and infrastructure to enable reliable analytics and data-driven decisions
• ETL/ELT Development: Build, optimise, and manage ETL processes in BigQuery and associated tools to ensure timely and accurate data ingestion
• Data Warehousing: Maintain and evolve our BigQuery data warehouse, ensuring it is performant, reliable, and aligned with business needs
• Data Quality and Governance: Implement data validation, monitoring, and governance processes to maintain high-quality and reliable datasets
• Cross-functional Collaboration: Work closely with teams across the organisation to support their data requirements and ensure alignment on data strategy
• Infrastructure Automation: Automate and streamline infrastructure deployment and management processes, improving operational efficiency

• Initial Call: Start with an introductory call with our Talent Acquisition Partner to discuss the role and your potential fit. (30 mins)
• Skills-Based Interview: Engage in a detailed discussion about your past experiences as well as completing a short assessment with one of our Tech Leads and Senior Data Engineer (1 hr)
• Final Values Interview: Final values interview and chat in-person at our London office with Head of Business Intelligence and our Chief Technology Officer