Manu Priyam Mittal

Senior Data Engineer at Innovation Refunds (2023-07 – Present)

Developed cost-efficient ETL pipeline (Tax Status API → VPC → Glue/Python → S3 → Redshift → dbt → Lambda/TypeScript → HubSpot) with runtime deduplication, automating IRS refund updates. Enabled timely payments and revenue growth, reducing peak-day ingestion costs by 90% (from $8K to $700/day) by replacing legacy Fivetran setup.
Enhanced fraud detection by streamlining company registration (AWS CDK → Lambda/Step Functions/TypeScript → Experian AMS → DynamoDB). Implemented modular, unit-tested services (Jest) and proactive monitoring (CloudWatch → Slack). Replaced Redshift with DynamoDB, cutting runtime from hours to minutes.
Automated leadership reporting by building a scheduled pipeline (Glue → S3 → Redshift → dbt → Lambda/TypeScript → SES) with email delivery, eliminating manual effort and enabling faster business decisions.
Built a centralized event logging mechanism (EventBridge → Firehose → S3 → Redshift) with batching, retries, and CloudWatch logging for reliable event delivery, enabling unified storage of all platform events.
Enabled ingestion of custom Sage fields via an automated pipeline (Sage API → Lambda/Fivetran Custom Connector → Redshift) with pagination and incremental processing, unlocking CRM (HubSpot) and Accounts (Sage) data joins to power critical business decisions.

Software Development Intern at Happay (MakeMyTrip) (2023-01 – 2023-06)

Boosted user engagement by adding WhatsApp notifications to SMS and push channels, ensuring timely expense alerts and approvals.
Built and deployed production-ready REST APIs using Python and Django, handling business logic for expense management workflows with PostgreSQL as the primary data store and Redis for caching and performance optimization.
Containerized services using Docker, ensuring consistent development and deployment environments across the team.

Quantitative Research Intern at JPMorgan Chase & Co. (2022-07 – 2022-12)

Developed a stress testing regression model as part of the CCAR (Comprehensive Capital Analysis and Review) exercise on a student loan portfolio, simulating adverse macroeconomic risk scenarios to assess portfolio resilience.
Engineered feature sets, ran analyses with Python (NumPy, Pandas, Matplotlib) to model macroeconomic variables and loan defaults. Documented methodology, assumptions, results in Excel, producing structured reports per regulatory standards.

Data Analysis Intern at PayPal India Development Centre (2020-05 – 2020-07)

Conducted comprehensive market research on India's digital wallet industry, analyzing competitive landscape, user adoption trends, and growth drivers across key players (Paytm, PhonePe, Google Pay, Amazon Pay). Leveraged qualitative methods (industry reports, expert interviews, customer sentiment analysis) and quantitative methods (market sizing, trend analysis, data modeling) to derive actionable insights.

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