Senior Data Engineer, Room Price Genie

• 4–5 years of professional experience in data engineering, with a proven track record of designing, building, and maintaining reliable data solutions in cloud environments
• Based in Greater London (hybrid), with the flexibility to meet the team in London once a week
• Strong experience with AWS services, including S3, Glue, Lambda, AppFlow, Athena, and CloudWatch, for building and monitoring scalable data pipelines
• Hands-on experience with Snowflake and dbt, and a solid understanding of modern ELT best practices and layered data architectures (bronze–silver–gold)
• Proficiency in Python and SQL for data ingestion, transformation, and workflow automation
• Deep understanding of data architecture principles, including data lakes, lakehouses, and warehouses, as well as schema design and data modeling best practices
• Experience with ingestion tooling such as Fivetran or AppFlow for integrating data from diverse sources
• Familiarity with Terraform (or other infrastructure-as-code tools) to ensure reproducible and version-controlled infrastructure management
• Strong documentation and process discipline, capable of creating scalable, maintainable, and repeatable systems
• Self-driven and proactive, with the ability to work autonomously and take end-to-end ownership of data solutions

Desirable

• We are building the analytics function from the ground up at RoomPriceGenie, and we’re looking for a highly capable Data Engineer to design and deliver our end-to-end data infrastructure
• This is a foundational role where you will architect the pipelines, schemas, and processes that power our data-driven decision-making
• Serves as the first data engineer dedicated to analytics, redefining the data pipeline and architecture to strengthen the company’s analytics capabilities
• Designs and owns a scalable analytics data architecture, including the implementation of a data lake, Iceberg tables, and a future Snowflake-based lakehouse
• Builds and maintains reliable data ingestion and transformation pipelines across product, sales, finance, and third-party systems using tools such as AWS Glue, AppFlow, Fivetran, and dbt
• Develops robust data models and schemas that follow best practices and support analytics, BI, and reporting needs
• Automates infrastructure and workflows using Python, Terraform, and AWS monitoring tools, ensuring scalability, stability, and reproducibility
• Documents data flows, pipelines, and standards, and collaborates with analysts, product managers, and leadership to ensure data is accurate, accessible, and actionable
• Continuously identifies opportunities to improve data quality, efficiency, and scalability