TechHive 
Transforming the Data Landscape for a Fashion Retail Giant
A veteran UK fashion retailer, in business for eight decades and operating 250+ stores across the UK and Europe, managing every stage from manufacturing and design to online and offline distribution.
Technologies Used
The Challenge
The client's data infrastructure was built on legacy Apache Airflow 1 running in Docker on EC2 — unscalable and prone to performance limits. A single team handled both ETL and corporate reporting, becoming a bottleneck for the whole business, with no UAT environment (changes went straight to production), manual Snowflake account creation, and no standard templates for tables, views, or permissions.
The Solution
We upgraded the client to Apache Airflow 2 across three proper environments — development, UAT, and production — with automated end-to-end testing built into CI, then shared the instance across 8 product teams so each could manage its own data loads independently. We split the data function into two focused teams, Data Engineering and Business Intelligence, and introduced a data ownership model so each product's data had a clear, responsive owner. Standardised dbt templates brought consistency to new models and views, while Terraform automated Snowflake account creation and IP allowlisting, backed by SSO and MFA for secure, centralised user administration.
The Results
- 60% more workload capacity, with the infrastructure adapting 40% faster to changing business needs.
- Bottlenecks eliminated — focused teams and decentralised data ownership sped up response times across the business.
- 25% fewer errors from standardised development processes.
- 50% lower risk of unauthorised access, thanks to automated account management, SSO, and MFA.