Data Engineer

• Build and maintain a modern, scalable data platform that supports growth and decision-making.
• Ensure data is accurate, consistent, and trusted across the business.
• Improve speed, reliability, and automation of data pipelines and reporting workflows.
• Enable high-quality self-serve analytics by delivering well-modelled, well-documented data sets.
• Support digital performance and CRM insight through strong marketing data foundations.
• Design, implement, and maintain robust data pipelines across multiple systems.
• Ensure smooth, well-governed flow of data from source → warehouse → BI layers.
• Support end-to-end warehouse design and modelling as our stack grows.
• Integrate and manage a wide range of data sources within Snowflake, including: Adalyser, Meta Ads, Google Ads, HubSpot, Aircall, Performance tracking data, Product imagery + metadata from bespoke internal platforms.
• Maintain consistency and quality across the ecosystem as new sources come online.
• Build automated checks to monitor accuracy, completeness, and freshness.
• Run regular audits and troubleshoot issues quickly and calmly.
• Create clear ownership and definitions for key data sets.
• Identify opportunities to streamline pipelines, improve performance, and reduce cost.
• Automate repetitive workflows to free teams up for higher-value analysis.
• Improve reliability and speed of reporting inputs.
• Work closely with teams across Growth, Finance, Ops, and Product to understand KPIs and reporting needs.
• Translate those needs into smart, scalable data solutions.
• Communicate clearly with both technical and non-technical folks, no jargon fog.
• Document architecture, pipelines, models, and workflows so everything is clear and easy to pick up.
• Contribute to data standards and governance as we build out the function.
• Share knowledge openly and help shape how data engineering is done at Vintage.com and Vintage Cash Cow.

Data Engineer

Data Engineer

Junior Data Engineer