# Experience — Divyanshu Tiwari

Hands-on work across data engineering, cloud pipelines, and analytics.

## Work History

### AI Data Engineer Intern — Zeitster
- **Period**: Aug 2026 – Present
- **Location**: Remote
- **Summary**:
  - Architected end-to-end ingestion pipelines for Shopify and merchant data using GraphQL Bulk Operations, Webhooks, S3, Lambda, SQS, Redshift, and Aurora.
  - Built ingestion flows for historical backfills and incremental syncs with idempotency, dead-letter queues, and reconciliation for dropped events.
  - Mapped data stages from raw ingest through validation, normalization, and canonical warehousing to final scoring tables.
  - Drafted canonical schemas and data contracts to unify Shopify, payment gateway, 3PL, and warehouse feeds.
  - Codified 20+ business-health formulas with explicit transformation logic, boundary checks, and fallback rules.
  - Engineered a Formula Dependency Registry to trigger recalculation only when upstream fields change.
  - Stress-tested formulas against synthetic edge cases (refunds, late webhooks, duplicate events, and partial payloads).
  - Benchmarked AWS compute and storage costs to model operating expenses scaling from 10 to 10,000 merchants.
  - Set up data-quality monitors and alert thresholds for ingestion latency, validation failures, and score drift.
- **Technologies**: AWS (S3, Lambda, SQS, Redshift), Aurora PostgreSQL, DynamoDB, Python, SQL, Shopify GraphQL, Data Modeling, Data Pipelines

### Data Analyst Intern — ChatSpark
- **Period**: Mar 2026 – May 2026
- **Location**: Remote
- **Summary**:
  - Automated weekly Excel reporting in Python, cutting report turnaround from 3+ hours to under 5 minutes.
  - Ran SQL cohort analyses on raw transactions, uncovering a 15% dip in 90-day repeat purchases to guide retention experiments.
  - Maintained core operational dashboards, keeping KPI feeds reliable for day-to-day decisions.
- **Technologies**: Python, SQL, Excel Automation, Cohort Analysis, Dashboards

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