Freshminds

Data Engineer - Retail

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer in the luxury retail industry, lasting 12 months with a pay rate of £50,000-£60,000. Key skills include Python, Snowflake, and MLOps principles, requiring 2-4 years of data engineering experience. Hybrid work, 2 days in London.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
-
💰 - Day rate
272
-
🗓️ - Date
May 23, 2026
🕒 - Duration
More than 6 months
-
🏝️ - Location
Hybrid
-
📄 - Contract
Fixed Term
-
🔒 - Security
Unknown
-
📍 - Location detailed
London Area, United Kingdom
-
🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Data Engineering #Python #Snowflake #Cloud #CRM (Customer Relationship Management) #ML (Machine Learning) #Data Science #Version Control #Monitoring
Role description
The Role A client in the luxury retail industry is seeking for a Data Engineer to join their team for 12 months. You will work closely with a global data function to productionise customer and CRM models, ensuring they run reliably at scale across regions. You will report into senior data stakeholders and support a wider transformation focused on building robust data platforms and enabling advanced customer insight and personalisation. Responsibilities • Build, deploy and maintain production-grade data and machine learning pipelines • Operationalise customer and CRM models to ensure consistent and reliable delivery • Implement monitoring, alerting and fallback processes to support pipeline performance • Collaborate with data scientists and regional stakeholders to troubleshoot and enhance data workflows Requirements • 2–4 years of experience in data engineering within a global organisation • Strong Python skills with experience supporting productionised data science models • Hands-on experience with Snowflake or similar cloud data platforms • Understanding of MLOps principles including testing, version control and monitoring Details • Start date: June 2026 • Duration: 12 months • Salary: £50,000- £60,000 • Location: Hybrid, 2 days per week in London