Dipendra P.
Yadav

Remote | Austin, TX

• ●Architected end-to-end enterprise data pipelines using PySpark, Hadoop, and Hive on AWS EMR, processing multi-TB insurance datasets to power analytics, reporting, and ML workloads.
• ●Spearheaded migration of core insurance data systems to AWS (S3, EMR, Glue, Redshift), designing ETL/ELT workflows that reduced data processing errors and testing cycles by 85%.
• ●Implemented data quality and governance frameworks — schema validation, null-rate monitoring, row-count reconciliation, and data lineage tracking — ensuring audit compliance in regulated environments.
• ●Designed star-schema and dimensional data models supporting Tableau and Power BI dashboards across underwriting, claims, and finance functions.
• ●Partnered with data scientists to build ML-ready feature pipelines ensuring point-in-time correctness and feature consistency between training and inference environments.
• ●Led and mentored a cross-functional Agile team, driving monthly insurance reports and data extracts with structured stakeholder reporting.
• ●Optimized Spark job performance via partition tuning, broadcast joins, data skew mitigation, and strategic caching — reducing runtimes and cluster costs for mission-critical batch workloads.

Founder & Engineering Lead

Queuella — Service Operations SaaS ↗

2024 – Present

Georgetown, TX

• ●Architected and directed development of a production multi-tenant SaaS platform (Next.js 16 / TypeScript / PostgreSQL) with a native Swift iOS companion app serving paying customers across the US, Nepal, and India.
• ●Designed a multi-service AWS backend: S3, SQS, SNS/SES, Cognito (including zero-data-loss migration from Clerk), ECS, Bedrock, and EventBridge.
• ●Integrated Square API across five surfaces (Catalog, Team Members, Labor, Locations, Payments) enabling automatic real-time sync of a client's full business profile on integration.
• ●Built a native iOS app (Swift, MVVM) with SSE streaming, APNs push notifications, Keychain auth, and deep link routing — published and serving live customers.
• ●Delivered full Stripe billing infrastructure: subscriptions, webhooks, usage-based billing, and multi-location pricing with a custom superadmin pricing editor.
• ●Established a production-grade testing strategy: Vitest unit suites across 8 domains and 20+ Playwright E2E suites covering auth, kiosk privacy, scheduling, and billing.

Engineering Lead — Business Automation

iBrows Studio | Multi-Location Beauty Brand

2024 – Present

Georgetown, TX

• ●Built a fully automated multi-location payroll processing system (Python, AWS Lambda, EventBridge cron) eliminating all manual payroll processing across bi-monthly pay cycles.
• ●Engineered a Square API pipeline consuming Labor API (timecards + break deduction), Team Members API, and Payments API — transforming raw data into fully computed payroll using pandas with per-employee rules.
• ●Built a timezone-aware timecard anomaly detection engine flagging clock-in/out violations, oversized shifts, and probable auto-clockouts with configurable grace windows.
• ●Delivered a three-tier email notification system: branded HTML pay stubs, timecard exception reports, and a full manager summary with payroll totals and outstanding issues.

Austin, TX

• ●Built a real-time pipeline for high-volume social media stream analysis using Apache Kafka and Spark Streaming, end-to-end from ingestion to output sink.
• ●Conducted large-scale COVID-19 data analysis on AWS EMR producing statistical insights and predictive model inputs from multi-source healthcare datasets.
• ●Developed Power BI dashboards for call center analytics, integrating multiple data sources and delivering BI reporting for business stakeholders.

Lubbock, TX

• ●Automated data extraction and processing pipelines from large-scale system log files using Python and Bash scripting, improving data accuracy and enabling structured analytical workflows.

Languages

Big Data

Cloud / AWS

Databases

APIs / Integration

AI / LLM

ETL / ELT

Data Quality

ML Frameworks

BI / Viz

DevOps / Other

Academy Accreditation — Databricks Lakehouse Fundamentals

Issued Oct 2022

Advances in Deep Learning

Issued Jan 2026

Design Principles & Causal Inference

Issued Dec 2024

Data Structures & Algorithms

Issued Dec 2024

Optimization

Issued May 2025

Deep Learning

Issued Aug 2024

Data Science for Health Discovery and Innovation

Issued May 2024

Foundations of Regression and Predictive Modeling

Issued May 2024

Machine Learning

Issued Dec 2021

Probability and Simulation-Based Inference

Issued Nov 2021