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Data Engineering

Fortune 500 company

Enterprise Data Warehouse & Analytics Platform

Built a BigQuery-centered warehouse with scheduled ETL, Streamlit dashboards, and unified reporting across four sources.

Case focus

Manual Excel reporting took weeks and KPI visibility was fragmented across multiple sources.

Challenge pressure

Manual Excel reporting took weeks and KPI visibility was fragmented across multiple sources.

Delivery response

Built a BigQuery-centered warehouse with scheduled ETL, Streamlit dashboards, and unified reporting across four sources.

Measured outcomes

Outcome 01

30+ KPI metrics automated

Outcome 02

95% reporting time reduction

Outcome 03

99.9% uptime for the analytics workflow

Technology stack

BigQueryPythonStreamlitDockerGCS

Delivery fit

Designed for Fortune 500 company where data engineering needed to feel like a dependable operating system, not a fragile prototype.

Case dossier

Client

Fortune 500 company

Category

Data Engineering

Outcome snapshot

  • 30+ KPI metrics automated
  • 95% reporting time reduction
  • 99.9% uptime for the analytics workflow

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