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prathamagrawal/README.md
β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—  β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•—β–ˆβ–ˆβ•—  β–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ•—   β–ˆβ–ˆβ–ˆβ•—
β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β•šβ•β•β–ˆβ–ˆβ•”β•β•β•β–ˆβ–ˆβ•‘  β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ–ˆβ–ˆβ•— β–ˆβ–ˆβ–ˆβ–ˆβ•‘
β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘   β–ˆβ–ˆβ•‘   β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β–ˆβ–ˆβ–ˆβ–ˆβ•”β–ˆβ–ˆβ•‘
β–ˆβ–ˆβ•”β•β•β•β• β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•—β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘   β–ˆβ–ˆβ•‘   β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•”β•β•β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘β•šβ–ˆβ–ˆβ•”β•β–ˆβ–ˆβ•‘
β–ˆβ–ˆβ•‘     β–ˆβ–ˆβ•‘  β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘  β–ˆβ–ˆβ•‘   β–ˆβ–ˆβ•‘   β–ˆβ–ˆβ•‘  β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘  β–ˆβ–ˆβ•‘β–ˆβ–ˆβ•‘ β•šβ•β• β–ˆβ–ˆβ•‘
β•šβ•β•     β•šβ•β•  β•šβ•β•β•šβ•β•  β•šβ•β•   β•šβ•β•   β•šβ•β•  β•šβ•β•β•šβ•β•  β•šβ•β•β•šβ•β•     β•šβ•β•

Software Engineer Β· Data Infrastructure Β· AI Systems

Email LinkedIn GitHub Kaggle Phone


> whoami

pratham = {
    "role"      : "Software Engineer @ Affinsys.ai",
    "location"  : "Bangalore, India",
    "education" : "B.Tech CS (Data Science) Β· VIT Vellore Β· CGPA 9.25",
    "focus"     : ["Data Infrastructure", "LLM Systems", "Distributed Architecture"],
    "prev"      : "SDE Intern @ CME Group",
    "open_to"   : "SDE-1 / Data Engineer roles Β· Bangalore / Delhi NCR",
}

Building systems where data pipelines meet intelligence — from NLQ→SQL platforms to event-driven warehouses, I ship infrastructure that scales and sticks.


> experience --verbose

🏒 Affinsys.ai Β Β·Β  Software Engineer Β Β·Β  Jan 2024 – Present

Service What I Built Impact
DBOps LLM-driven system using Claude to synthesize executable ETL pipelines from natural language, with schema validation & iterative correction loops Reliable NL→ETL at scale
Datalens NLQβ†’SQL analytics platform with secure sanitisation, metadata-driven query gen, reusable chart catalogs & 15+ dynamic chart types ↓ 80% dashboard creation time
Analytics End-to-end service powering 20+ dashboards & 200+ charts with real-time insights, materialized SQL views, and an automated report scheduler for 100+ recurring reports ↓ 40% query overload
Archival Distributed archiving across 10+ services β€” referential integrity, failover strategy, purge algorithm, MinIO β†’ AWS S3 migration Zero data loss guarantee
Eventlogger High-performance event-driven data warehouse aggregating from 10+ services (AMQP/NATS) into 40+ tables with async writes Rapid cross-service analytics

🏒 CME Group Β Β·Β  SDE Intern Β Β·Β  May 2023 – Nov 2023

  • Re-engineered critical report & email generation algorithms β†’ ↑ 30% performance
  • Built advanced data extraction & processing tools β†’ ↓ 40% latency

> projects --pinned

πŸ—„οΈ Mirror-DB

Kubernetes Β· PostgreSQL Β· PgBouncer Β· Helm

Enterprise-grade PostgreSQL HA cluster with:

  • ⚑ Sub-minute automatic failover
  • πŸ”Œ 70–90% connection overhead reduction via PgBouncer
  • πŸ”„ Multi-tier sync/async replication across 4-node cluster
  • 🏷️ Dynamic service discovery with automated pod labeling
  • πŸ“Š Comprehensive monitoring stack

πŸͺ΅ LogHive

Python Β· RabbitMQ Β· Redis Β· PostgreSQL Β· Docker

Scalable log archival system built for the long haul:

  • 🌊 Handles petabyte-scale data
  • βœ… 99.99% reliability with advanced compression
  • πŸ“ˆ Adaptive consumer scaling & producer rate limiting
  • πŸ›‘οΈ Prevents system overload under burst traffic

> tech_stack --list-all

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  LANGUAGES        Python Β· Golang Β· C Β· C++ Β· SQL               β”‚
β”‚  DATABASES        PostgreSQL Β· Oracle Β· MongoDB Β· Data Warehouse β”‚
β”‚  STREAMING        Kafka Β· RabbitMQ Β· NATS Β· AMQP                β”‚
β”‚  DATA SCIENCE     Apache Airflow Β· Spark Β· Hadoop Β· Astro        β”‚
β”‚  CLOUD & INFRA    AWS Β· Docker Β· Kubernetes Β· GitHub Actions     β”‚
β”‚  OBSERVABILITY    Tableau Β· Materialized Views Β· Custom Metrics  β”‚
│  AI/LLM           Claude API · NLQ→SQL · ETL Pipeline Gen        │
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Python Go PostgreSQL Kafka Docker Kubernetes AWS Apache Spark Apache Airflow Redis RabbitMQ MongoDB


> achievements --highlight

πŸ†  Chairperson @ IET-VIT
    └── Hosted technical events Β· 25% net profit Β· Mentored 200+ members

πŸ₯‰  3rd Place Β· TRI-NIT Hackathon 2023
    └── Project: Clusterbase

πŸ₯‡  Sponsor Track Winner Β· Devspace 2022 by CSI-VIT
    └── Project: Sportlight

πŸŽ–οΈ  Google Cloud Computing Foundations β€” Certified
πŸ…  Kaggle Contributor β€” 4Γ— Bronze Medal (Notebooks & Datasets)

> github --stats

Β Β 

"Ship infrastructure that outlasts the sprint."

Open to SDE-1 & Data Engineer roles Β· Bangalore / Delhi NCR

Email Me Connect

Pinned Loading

  1. mirror-db mirror-db Public

    This repository contains a comprehensive PostgreSQL High Availability setup using **pg_auto_failover** with **PgBouncer** connection pooling on Kubernetes. The cluster provides automatic failover, …

    Shell

  2. LogHive LogHive Public

    Python 2 1

  3. ClusterBase ClusterBase Public

    Forked from 1407arjun/TRINIT-Conda-Activate-Venv-DEV04

    Clusterbase is a system that is easily configurable on the number and type of parameters and clustering rules, where in the clustering happens in real time with the values dynamically provided by t…

    TypeScript

  4. Crypto2csv Crypto2csv Public

    Crypto2csv is a python package accessible via command line for accessing crytocurrencies data in a readable csv format.

    Python 1

  5. sportlight sportlight Public

    Forked from 1407arjun/sportlight

    A solution for highlights extraction for sports games by The Unknowns.

    JavaScript

  6. Analysing-Olympics-Dataset Analysing-Olympics-Dataset Public

    Jupyter Notebook 3