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Data Platform

Data Platform and Analytics Scale-Up for a Premium Fashion Brand

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2025-06-01
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7 min
Wasle

Mission Overview

Mission Title Data Platform and Analytics Scale-Up
Client CTO (confidential fast-growing premium fashion brand)
Type of Profile Lead Data Engineer and Analytics Lead (interim, hands-on)
Duration Multi-quarter engagement (build + rollout)
Core Stack Snowflake, dbt, Airflow, Power BI

Context

The brand was scaling fast across retail and ecommerce. Data was fragmented across business tools, creating inconsistent reporting, slow decision cycles, and limited trust in numbers. The goal was to build a single source of truth and deliver executive-grade analytics across teams.

What We Built

Workstream Delivery Impact
Data Foundation Snowflake warehouse with a medallion-style model layer in dbt, production-ready standards Reliable source of truth and scalable structure for new domains
Ingestion and Orchestration Automated pipelines with Airflow, including enterprise source feeds and operational workflows Faster refresh cycles and reduced manual dependencies
Business Models Large-scale dbt modeling effort, including analytics-ready marts for core functions Consistent definitions and reusable metrics
Analytics and Dashboards Power BI datasets designed for executive, operational, and functional reporting Clear visibility across retail, ecommerce, CRM, finance, and supply
Self-Service Enablement Exploration of search and self-service BI patterns for non-technical users Improved adoption and reduced reporting bottlenecks

Key Deliverables

  • 149 dbt models deployed on Snowflake, structured to support scale and governance
  • 21 integrated data sources across operational and growth systems
  • 31 Power BI datasets covering CRM, retail, ecommerce, finance, supply, wholesale, and leadership reporting
  • Automation of critical workflows, including enterprise operational inputs and collaboration tooling

How We Worked

  • Direct collaboration with the CTO and transformation stakeholders
  • Weekly prioritisation based on business impact and operational urgency
  • Production standards: naming conventions, model layering, release discipline, and documentation
  • Adoption-first dashboards: fewer metrics, clearer ownership, faster decisions

Results

  • One trusted reporting layer across functions
  • Faster delivery of new analytics use cases and fewer ad-hoc requests
  • Improved decision cadence across commercial and operational teams
“Wasle built a reliable data foundation fast and turned it into dashboards our teams actually use.”

CTO, Premium Fashion Brand

We built a reliable data foundation fast and turned it into dashboards our teams actually use.

Tech Lead, Premium Fashion Brand
Conclusion
A modern, scalable data stack that aligned retail, ecommerce, CRM, finance, and marketing into one source of truth, with measurable execution speed and stronger decision-making.

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