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Smit Patel

Data Analyst & Data Engineer. I design reliable data pipelines, APIs, and dashboards that reduce cycle times and cost. Comfortable across Python, SQL, JavaScript, React, Node.js, Power BI, and AWS. I enjoy turning ambiguous problems into measurable wins.

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Essential Recruiter Signals

- Impact: cost savings, latency/throughput wins, incident ownership
- Reliability: tests, CI/CD, monitoring, rollbacks
- Data quality: validation, schema governance, SLAs
- Architecture: modular design, API contracts, versioning
- Communication: stakeholder updates and docs

Reliability

99.9% uptime

Scale

1.5k+ req/day

Delivery

12+ dashboards

Core Skills

quick overview

Programming

Python TypeScript/JavaScript Java SQL R

Frontend

React Next.js TailwindCSS

Backend & APIs

Node.js FastAPI REST GraphQL (basic)

Data & Analytics

Pandas NumPy scikit-learn Power BI Tableau

Data Engineering

Airflow dbt (basic) Kafka Spark Delta Lake

Cloud & DevOps

AWS (S3, Lambda, EC2, IAM, CloudWatch) Docker Kubernetes GitHub Actions Terraform (basic)

Databases & Storage

PostgreSQL MySQL MongoDB Redis DynamoDB

Quality & Observability

Jest Pytest CI/CD logging/metrics/tracing

Security & Privacy

OAuth2/JWT secrets management least privilege PII handling

Collaboration

Git Jira Confluence Agile/Scrum

Education

Master of Applied Computing, University of Windsor

May 2024 – Dec 2025 — Current average 88.4%.

B.E. Computer Science, Gujarat Technological University

Jul 2019 – May 2023 — Current average 87.5%.

Projects

All Projects
Valorant Stats Tracker React Native + AWS (Private)

Valorant Stats Tracker — RN + AWS (Private)

Cross-platform app (iOS/Android) with real-time player insights; authorized Riot Games API access.

  • RN + TypeScript UI; agent/map/weapon analytics & interactive dashboards.
  • Backend: AWS Amplify (auth/sync), DynamoDB, Lambda, Kafka streaming.
  • Pipeline: batch + caching + real-time updates.
  • 15k+ installs, 1k+ DAU, ⭐ 4.5, 99.9% uptime, ~1.8s avg response.
React Native TypeScript Riot Games API AWS Amplify DynamoDB Lambda Kafka
README
Contact Me
ByteNode — IPFS Storage Distributed System

ByteNode — IPFS Distributed Storage System

Django-based storage that chunks files, stores redundant copies across IPFS nodes, and self-heals with health checks and auto-rebalancing.

  • Secure auth + role-based access; REST API & admin dashboard.
  • 1MB intelligent chunking; multi-node redundancy & fault tolerance.
  • check_system_health detects/repairs missing chunks; automatic rebalancing.
  • Monitoring & self-healing with scheduled integrity checks.
Django IPFS PostgreSQL REST Chunking Redundancy Self-Healing
Repo
SkillXChange Peer-to-Peer Learning

SkillXChange — Peer-to-Peer Learning

Credit-based learning platform with secure auth, rich profiles, networking, chat, and ZEGOCLOUD video for live sessions.

  • Earn/spend credits for lessons; inclusive, non-monetary model.
  • Profiles, ratings, and skill promotion; LinkedIn-style networking.
  • Real-time chat + ZEGOCLOUD video; advanced search by skill, location, reviews.
  • Aligned with UN SDG-4: equitable access & lifelong learning.
Django PostgreSQL REST Auth jQuery ZEGOCLOUD Search
Repo
Fraud Detection ML Baselines & Ensemble

Fraud Detection on BankSim — ML Baselines & Ensemble

End-to-end ML pipeline using KNN, XGBoost, RandomForest, and an ensemble; SMOTE variant included for balanced classes and improved recall.

  • EDA + feature engineering on synthetic BankSim payments.
  • Reports for KNN/XGB/RF + ensemble with confusion matrices.
  • SMOTE notebook adds balanced-class runs with stronger minority recall.
  • Kaggle reference and original paper cited in repo.
Python Pandas scikit-learn XGBoost KNN RandomForest SMOTE Jupyter
Repo
Car Rental Intelligence Advanced DSA in Java

Car Rental Intelligence — Advanced DSA in Java

Java application that crawls listings, ranks and filters cars, and powers fast search via advanced data structures and algorithms.

  • Selenium crawler with popup handling; URL extraction from CSV.
  • Search frequency with AVL/Red-Black trees; Inverted Index for fast lookup.
  • Spell-checker: Cuckoo Hash, Edit Distance, Merge Sort for suggestions.
  • Ranking & filters: Boyer–Moore (frequency), Quick Sort (ratings desc).
Java Selenium AVL Tree Red-Black Tree Cuckoo Hash Edit Distance Boyer–Moore Merge Sort Quick Sort Inverted Index
Repo
Realtime Group Chat Flutter + Firebase

Realtime Group Chat — Flutter + Firebase

Cross-platform group chat with auth, reactions, media, and real-time updates.

  • Auth (email/password), profile setup, message reactions (long-press).
  • Firestore realtime chat, Cloud Functions, Storage, FCM notifications.
  • Clean, smooth UI/UX; mobile/web/desktop from one codebase.
Flutter Dart Firebase Auth Firestore Cloud Functions Storage FCM
Repo

*Demo videos available in respective project README files.

Experience

  1. System & Data Analyst Intern — University of Windsor (May 2025 – Present)

    Python Power BI SQL AWS (S3/Lambda/CloudWatch) Data Visualization Workflow Automation

    Campaign analytics in 20+ countries; automated reimbursements, cost controls, and KPI ROI visibility.

    • - Built an automated reimbursement system, cutting processing time by ~40% using SQL + Python.
    • - Optimized subscription/licensing, saving $15k/year while retaining full functionality.
    • - Delivered self-serve KPI scorecards and Power BI dashboards for campaign, travel, and recruiter performance.
    • - Applied governance/validation rules across multi-regional datasets, improving reporting consistency by ~25%.
    • - Designed a data-quality framework with anomaly checks, reducing BI data failures by ~60%.
    • - “Light AWS”: S3 + Lambda + CloudWatch for scheduled jobs, alerts, and monitoring.

  2. Software Developer — BarodaWeb (Jan 2023 – Apr 2024)

    Kotlin Flutter React Django FastAPI Docker GitHub Actions

    Mobile + microservices delivery (1.5k+ req/day, 99.9% uptime), AI extension, and CI/CD.

    • - Shipped production mobile features in Kotlin/Jetpack Compose & Flutter, improving startup by ~20% and achieving 99.5% crash-free sessions.
    • - Adopted MVVM + Clean Architecture with Hilt DI to scale feature delivery.
    • - Built microservices in Django + FastAPI handling 1,500+ daily requests at 99.9% uptime; added JWT + RBAC for 500+ users.
    • - Migrated a legacy monolith to GDPR-compliant services, cutting API response time by ~65%.
    • - Integrated REST via Retrofit with offline caching (Room/DataStore) and robust error handling.
    • - Built an AI-powered Chrome extension (React + Python NLP) for JD analysis, adopted by 200+ recruiters.
    • - Automated CI/CD with GitHub Actions, Dockerized deployments on Linode, and feature flags for safe releases.

Blog

More on Medium

More case studies coming soon

ETL with Airflow/dbt, FastAPI microservice, and a Docker/K8s deploy write-up.

Coming Soon

Interested in collaborating or have questions?

I’m open to data and data-engineering roles. Quick responses, clear communication.

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