Himanshu Pant

About

Engineer at heart.

Data Engineer with expertise in large-scale data infrastructure, real-time processing, and AI/ML systems. I've migrated 1B+ records to distributed architectures, eliminated 90-minute production bottlenecks, and built real-time pipelines handling 500K+ daily events with 99.9% accuracy.

Track record of rapid impact across insurance, sports analytics, and healthcare — promoted within 6 months at Super Six and received SPOT Recognition Award for delivering critical data infrastructure under tight deadlines.

🏥 Healthcare⚽ Sports Analytics🏦 Insurance & Banking📊 Retention & Segmentation

100M-1B

Records Processed

M.S.

Software Engineering (AI Specialization) — Arizona State University

Tech I work with

Languages

PythonSQLJavaScriptPySpark

Data & ML

Apache SparkDatabricksAirflowLangChainSnowflakeGreat Expectations

Cloud & Infra

AWS (EMR, S3, Lambda, SQS, ECR)AzureDockerJenkinsCI/CD

Frontend

ReactNext.jsNode.jsHTML/CSS

Databases

PostgreSQLSQL ServerOracleNoSQLVector DBs

Tools

GitPower BIStreamlitJira

Achievements

Highlights.

🏆

DEVHACKS 2026 — 1st Place

Won Track 1 with MeetFlow — intelligent task orchestration converting meeting transcripts into capacity-aware ticket assignments using LLM-powered analysis, competing against 100+ teams.

☁️

AWS Certified Data Engineer Associate

Passed DEA-C01 (May 2026) — validated expertise in data pipeline design, ETL optimization, AWS Glue/EMR/Redshift, and implementing data quality frameworks at scale.

📊

Microsoft Certified: Fabric Analytics Engineer

Passed DP-700 (May 2026) — validated expertise in Microsoft Fabric analytics engineering, data warehousing, and cloud data solutions.

🏆

HackASU — FairCharge

Built a medical bill audit pipeline at HackASU that uses Claude Vision + SapBERT to detect overcharges, flagging $1,300+ in average billing errors per hospital bill.

🏅

SPOT Award — Exceptional Delivery

Recognized at Super Six Sports Gaming for exceptional delivery and cross-team collaboration on critical product features.

Certifications

Industry Credentials.

AWS Certified Data Engineer – Associate

Amazon Web Services • DEA-C01

Validated expertise in designing, building, and maintaining data pipelines using AWS services including Glue, EMR, Redshift, Kinesis, and implementing data quality frameworks at scale.

Microsoft Certified: Fabric Analytics Engineer Associate

Microsoft • DP-700

Certified in Microsoft Fabric analytics engineering, data warehousing, data modeling, and implementing end-to-end analytics solutions on Azure cloud platform.

Experience

Where I've worked.

Data & AI Engineer (Industry Capstone)

MyEdMaster

Jan 2026 – Apr 2026

Tempe, AZ

Developed multi-agent stateful RAG system for personalized legal guidance using LangGraph and Qdrant vector DB, achieving sub-2s query latency across 10K+ documents and 95% relevance accuracy
Built FastAPI + Node.js backend with Docker supporting 100+ concurrent sessions at sub-200ms response time via optimized retrieval and a 5-node pipeline
Authored evaluation framework for the QnA service and resolved critical production NameError in the agentic graph execution layer; shipped 4-layer technical documentation adopted by partner team

PythonLangGraphQdrantFastAPINode.jsDocker

Consultant II, Data Analytics & Engineering

EXL Services

Jul 2023 – Mar 2024

Gurugram, India

Eliminated a 90-minute production bottleneck by optimizing PySpark ETL on AWS Glue / MWAA processing 100M+ records per batch, cutting runtimes 66% via partition pruning
Architected S3 data lake and Snowflake warehouse across 8 datasets for 500K+ daily users on high-frequency insurance claim events, driving 40% BI query performance improvement
Built production data quality framework using Great Expectations across 15+ data sources with CloudWatch monitoring, maintaining 100% SLA compliance
Automated infrastructure provisioning by deploying Airflow DAGs via Terraform IaC and integrating Jenkins CI/CD with unit and integration testing

PySparkAWS GlueMWAASnowflakeS3Great ExpectationsCloudWatchTerraformJenkins

Data Engineer

Super Six Sports Gaming

Aug 2022 – Jul 2023

Gurugram, India

Built and owned the core data ingestion layer: multi-source batch ETL from 10+ REST APIs and S3, loading 500K+ daily records of sports event data into MongoDB with 99.9% accuracy
Reduced user churn 20% by building a production ML retention pipeline (78% accuracy, Scikit-Learn) detecting behavioral anomalies in time-series user activity and triggering automated Python/SQL workflows
Engineered ML feature pipelines with SCD Type 1/2 dimensional modeling, accelerating ML experiment cycle time by 35%

PythonSQLPySparkMongoDBS3REST APIsScikit-Learn

Associate Data Engineer

Futurense Technologies

Oct 2021 – Jul 2022

Bangalore, India

Spearheaded migration of 1B+ record oncology pipelines from legacy SAS to Apache Spark on Azure Databricks, cutting batch time from 6+ hours to 50 minutes (86% reduction) via broadcast joins
Automated bi-weekly HCP targeting reports via Python ETL on AWS Athena, reducing manual effort from 4-5 hours to 15 minutes (95% savings)
Delivered 99.5% data accuracy post-migration via comprehensive PySpark + SQL validation frameworks with statistical reconciliation

Apache SparkAzure DatabricksPySparkPythonSQLAWS Athena

Data Analyst

Koron Projects Limited

Oct 2018 – Jul 2021

New Delhi, India

Built 15 Power BI dashboards with advanced analytics for executive leadership tracking project costs, timelines, and profitability across $50M+ in annual construction projects
Consolidated cost data from SQL Server, Oracle, and MySQL via SQL and stored procedures, removing 20 hours/month of manual effort

Power BISQL ServerOracleMySQLSQL

Projects

Selected work.

FairChargeHackathon

Solo builder — HackASU Claude AI Builder Hackathon

A medical bill audit pipeline that reads your bill, identifies every charge, benchmarks against real CMS Medicare pricing data for your state, detects overcharges and billing violations, and generates a ready-to-send dispute letter. Built to fight the information asymmetry where 49–80% of medical bills contain errors.

Bill Upload & Analysis

1 / 3

PythonClaude VisionSapBERTChromaDBSQLiteStreamlitCMS Data

Code

MeetFlowHackathon Winner

Led the LLM pipeline & orchestration layer

Intelligent task orchestration that converts meeting transcripts into actionable tickets. Analyzes via GPT-4o-mini, checks team capacity through Taiga, recommends smart reassignment for overloaded members, and notifies via Slack.

Agent 1: Transcript Analysis

1 / 3

PythonStreamlitOpenAITaiga APISlack

Code

Serverless Face RecognitionAcademic

A serverless, multistage face recognition system using edge computing. IoT clients send video frames processed through decoupled detection and recognition stages via event-driven architecture — scalable, real-time identification without persistent servers.

AWS LambdaSQSECRDockerPyTorchOpenCVEdge Computing

LifeSyncLive

Full-stack productivity platform with Google OAuth, Focus Score tracking, daily task management, Pomodoro timer, and motivational micro-challenges.

Focus Score Dashboard

1 / 2

ReactNode.jsGoogle OAuthREST API

Live

The Pause ButtonLive

A developer wellness app with mixable ambient soundscapes, 10+ casual mini-games, and a calming UI — because even builders need a break.

Nature Sounds Mixer

1 / 2

ReactJavaScriptWeb Audio APICSS Animations

Live

Legal AI — Agentic RAGBuilding

Multi-agent system providing accessible legal guidance for those who can't afford a lawyer. Extensive query refinement via vector DB, specialized agents that collaborate independently.

PythonLangChainVector DBMulti-AgentLLM

Feature Store with Time TravelIndustry

Centralized Feature Store using Apache Iceberg with time-travel, enabling ML teams to train, test, and deploy from a single source of truth.

Apache IcebergSparkPythonML Infra

SAS to Spark MigrationIndustry

Migrated 50 legacy SAS workflows to Spark, cutting runtime from 6+ hours to under 50 minutes via partitioning, broadcast joins, and caching.

Apache SparkPySparkSASData Engineering

I build things that scale.