Data Engineer

Data Engineer Liquidline is the fastest-growing commercial coffee solutions provider in the UK and Ireland—not that we’re bragging! Our customers are companies that take pride in offering quality refreshments to their employees and clients. Our success is built on outstanding customer service, hard work, and a strong team culture. We believe in delivering WOW experiences to both our customers and our valued employees. We are proud to be Great Place to Work certified, a testament to our dedication to fostering a culture of support, growth and development, as well as promoting well-being, and winning together. With our core company values—passion, thoughtfulness, responsiveness, innovation, and smart working—at the very heart of our business, we are committed to cultivating an environment that inspires excellence. We’re looking for a Data Engineer to play a pivotal role in transforming Liquidline’s data landscape. You’ll take ownership of the technical foundations of our data platform – from ingestion and infrastructure to deployment – helping us move from legacy, on-premise systems to a modern, cloud-first data architecture. Working closely with the BI & Data Lead and an Analytics Engineer, you’ll be the primary architect of our new data platform, supporting our acquisition strategy and turning fragmented legacy data into a competitive, AI-ready asset. If you enjoy building things from the ground up, modernising complex systems, and shaping how data is used across a business, this role offers real ownership and influence. The Responsibilities of the Data Engineer

Designing a greenfield data platform – building and shaping our modern data stack (e.g. BigQuery, Airbyte), moving beyond standalone SQL Server environments. Leading integrations – supporting our NetSuite migration and creating scalable data frameworks for future acquisitions. Modernising legacy systems – refactoring complex, business-critical T-SQL into modular, high-performance cloud workflows. Raising engineering standards – introducing Git, CI/CD pipelines, automated testing and best-practice engineering processes. Preparing data for AI and ML – designing resilient architectures that ensure high-quality, accessible data for future AI initiatives.

What You Will Need In The Role Of Data Engineer

3–5+ years’ experience in Data Engineering, ideally involving cloud warehouse builds or migrations Expert-level SQL/T-SQL with proven experience refactoring and optimising complex logic Hands-on experience with cloud data warehouses (e.g. BigQuery, Snowflake), ingestion tools (Airflow, Airbyte), and analytics tooling such as dbt and Power BI Strong working knowledge of Git/version control, CI/CD pipelines, and Python for automation Solid understanding of star schemas and Kimball methodologies Experience supporting advanced Power BI models (DAX and Power Query) Exposure to ML/AI concepts (e.g. scikit-learn, TensorFlow) or an interest in preparing data for LLMs, RAG architectures or predictive models Experience with Docker and/or Terraform (desirable)