Data Engineer – Customer Data Pipelines & Analytics

THG; Manchester; On-site; GBP 55,000 - 75,000; Full time

Benefits offered by this job

Annual leave 25 days + holidays

Enhanced maternity/paternity pay

On-site gym

Staff discount on THG brands

On-site staff shop

Volunteer leave available

Job summary

THG, a global ecommerce group, is seeking a Data Engineer in the Customer domain to build and maintain data pipelines powering customer analytics across THG Beauty and THG Nutrition. You’ll work closely with the Senior Data Engineer to deliver a reliable, well-structured customer data layer.

You’ll develop expertise in the Customer data domain (CRM, acquisition, identity and marketing data flows) and apply engineering best practices, with increasing responsibility over time.

Qualifications

• Some experience or strong foundational knowledge in data engineering — Python and SQL are essential.
• Understanding of data pipeline concepts
• Curiosity and drive to develop as a data engineer
• Attention to detail and commitment to accurate, reliable work
• Ability to work collaboratively within a small team

Responsibilities

• Build and maintain data pipelines in the Customer domain under the direction of the Senior Data Engineer
• Write clean, well-documented SQL and Python code that meets the team’s standards
• Support the monitoring and resolution of pipeline issues
• Contribute to data quality checks and validation in the Customer domain
• Collaborate with Data Engineers and the Senior Data Engineer to support analytics teams with data requests

Skills

Python

SQL

Data pipelines

Data engineering fundamentals

Attention to detail

Tools

GCP/BigQuery

Git

Airflow

Job description

THG, a global ecommerce group, is seeking a Data Engineer in the Customer domain to build and maintain data pipelines powering customer analytics across THG Beauty and THG Nutrition. You’ll work closely with the Senior Data Engineer to deliver a reliable, well-structured customer data layer.

You’ll develop expertise in the Customer data domain (CRM, acquisition, identity and marketing data flows) and apply engineering best practices, with increasing responsibility over time.