Data Engineering for E-commerce

E-commerce platforms generate massive event volumes — hundreds of millions of daily transactions, clicks, and delivery updates that need processing with minimal latency. I optimize data pipelines for food delivery platforms, retail analytics, and marketing attribution systems where delayed insights directly translate to lost revenue. Whether it is reducing Snowflake compute costs by $140K annually or cutting insight delivery from days to hours, I build data infrastructure that keeps pace with high-velocity commerce.

E-commerce Data Challenges I Solve

Processing 100M+ daily events with sub-minute latency requirements

Balancing warehouse compute costs against real-time analytics demands

Multi-touch attribution across fragmented marketing channels

Maintaining 99.99% pipeline uptime during peak traffic periods

E-commerce Projects

Food Delivery Analytics Platform Optimizations

Batch processing system handling millions of daily events for premier food delivery service

100M+ Events/Day$140K Annual Savings99.99% Uptime
PythonAirflowSnowflakeDockerGrafana

Technologies I Use for E-commerce

Apache AirflowSnowflakePython

Building Data Infrastructure for E-commerce?

Let's discuss how modern data engineering can solve your e-commerce data challenges.

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