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Data Engineering
Retail
Northwind Analytics Cloud
A modern lakehouse serving 40,000 stores in real time.
Client
Northwind Retail Group
Delivered
2025 · 9 months
Team
12 engineers
Category
Data Engineering
Overview
What we built
Rebuilt Northwind's legacy on-premise analytics stack into a Databricks lakehouse serving sub-second dashboards to 40,000 stores across three continents.
Business impact
Outcomes that moved the P&L
0x
Faster reporting
0%
Lower TCO
0k+
Stores served
0
Reports migrated
The challenge
- Nightly ETL jobs took 11 hours and regularly missed store-open SLAs.
- Reporting was fragmented across 6 regional data warehouses with divergent metrics.
- Data platform costs were growing 34% year-over-year with no clear owner.
How we approached it
- Adopted a medallion architecture on Databricks with dbt for governed transformations.
- Built a unified semantic layer so every region measures revenue, margin and inventory the same way.
- Migrated 220 legacy reports with a phased cutover and dual-run validation.
What changed
- Dashboards load in under 800ms for store managers.
- Total data platform spend down 38% within the first year.
- Finance, merchandising and supply chain now trust a single set of numbers.
Project gallery
Inside the delivery
Unified semantic layer
One version of revenue, margin and inventory.
Store operations dashboard
Real-time KPIs for 40k store managers.
Data quality control plane
SLA-tracked pipelines with lineage.
Technology
Built with
The tools and platforms we chose for this engagement.
Databricks
dbt
Apache Airflow
AWS S3
Snowflake
Looker
Terraform
"Dataamps replaced a decade of legacy plumbing with something our teams actually love using. The ROI showed up in the first quarter."
Priya Menon — VP Data & Analytics, Northwind Retail Group
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