Context
Bulk operational data delivered as large CSV files.
Problem
Raw CSV data was difficult to clean, query, and reuse.
Constraints
Files were too large for ad-hoc processing and required repeatability.
Scope
Data engineer responsible for ingestion and transformation processes.
Strategy
Stage raw files in object storage and transform them into queryable columnar formats.
Architecture
Implemented cloud storage ingestion with downstream transformation into analytical data stores.
Impact
Enabled scalable querying and reuse of previously unwieldy datasets.
Effects
Accelerated marketing and analytics workflows dependent on clean lists.
Artifacts
CSV ingestion pipeline
Available upon request
Data cleaning and export process
Available upon request
Key Insights
Data usability depends more on format than volume.