Hi, I am

Manoj Bhatt

Senior Python Software Engineer

6.5+ years of experience building high-throughput data pipelines, web scraping systems, and scalable backend infrastructure using Python, Django, PostgreSQL, Scrapy, and AWS.

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Professional Summary

Results-driven Python Senior Developer with 6.5+ years of experience building high-throughput data pipelines, web scraping systems, and scalable backend infrastructure. Skilled in Python, Django, PostgreSQL, Scrapy, and Playwright, with expertise in ETL automation, large-scale data processing, API development, and performance optimization. Experienced with AWS and production deployments, with a strong focus on reliability, efficiency, and clean architecture. Passionate about solving complex engineering challenges, mentoring developers, and delivering high-impact solutions.

Technical Skills

Languages

Python SQL

Backend & Frameworks

Django Django REST Framework (DRF) Asynchronous Programming (AsyncIO)

Databases & Search

PostgreSQL (Optimization, Partitioning) Elasticsearch

Infrastructure & Cloud

AWS (EC2, S3, CloudWatch) Infrastructure Automation

Data Engineering

ETL Pipelines Apache Airflow Web Scraping (Scrapy, Playwright)

Tools & Methodologies

REST APIs Microservices Prompt Engineering (LLMs) Git

Experience

Software Engineer III

Contify

Oct 2025 - Present

Software Engineer II

Contify

Aug 2023 - Oct 2025

Software Developer

Contify

Dec 2019 - Aug 2023

Software Developer Intern

Stackmindz

Jun 2019 - Aug 2019

Featured Projects

High-Volume Data Pipeline & PostgreSQL Optimization

  • Architected a time-based partitioned PostgreSQL schema for 500GB+ of data, enabling efficient query execution at 500 QPS through advanced SQL and resource tuning.
  • Reduced average query response time by over 60% post-partitioning by aligning partition keys with the most frequent access patterns and eliminating full-table scans.
  • Implemented database indexing strategies and connection pooling to sustain throughput under concurrent load from multiple ingestion and read services.
PostgreSQL Optimization High Throughput

Enterprise Web Scraping & Data Extraction Platform

  • Built a multi-source data extraction system using Scrapy and Airflow, implementing proxy rotation and resilience patterns to handle complex, protected data sources at scale.
  • Designed a modular spider architecture allowing rapid onboarding of new data sources with minimal code changes, significantly increasing team throughput for coverage expansion.
  • Integrated Airflow DAGs for scheduling, retry logic, and alerting, improving pipeline observability and reducing data freshness lag across hundreds of concurrent scraping jobs.
Scrapy Airflow Data Extraction

AI-Powered PDF Summarization Microservice

  • Developed an asynchronous microservice using Django REST Framework and the OpenAI API, automating intelligent document extraction and summarization.
  • Implemented async task queuing to decouple PDF ingestion from summarization, enabling the service to handle burst traffic without blocking upstream workflows.
  • Designed a structured output schema for summaries, enabling downstream systems to index, search, and surface document insights through the intelligence platform.
Django REST OpenAI API Async Queuing

AWS Cloud Infrastructure & Automation

  • Managed scalable cloud infrastructure (AWS EC2, S3, CloudWatch), optimizing AMI lifecycle and vertical scaling to ensure high availability for critical data processing workloads.
  • Set up CloudWatch alarms and custom dashboards to proactively monitor instance health, reducing incident response time and minimizing unplanned downtime.
  • Automated AMI snapshot creation and rotation policies, reducing infrastructure provisioning time and ensuring consistent, repeatable deployment environments.
AWS EC2/S3 CloudWatch Automation

LLM-Driven Data Tagging & Post-Processing

  • Designed an automated pipeline for post-processing extracted data, leveraging LLMs to assign relevant categorization tags and significantly improve search relevance and data discoverability.
  • Optimized prompt engineering and implemented caching strategies to minimize API latency and operational costs while maintaining high classification precision.
  • Built an evaluation framework to measure tagging accuracy against a labelled validation set, enabling continuous prompt iteration and quality assurance at scale.
  • Integrated the tagging pipeline with Elasticsearch to surface categorized content through faceted search, directly improving end-user discoverability of intelligence data.
LLMs Prompt Engineering Elasticsearch

Education

Master of Computer Applications (MCA)

Amrapali Institute of Technology and Sciences, Haldwani

2017 - 2019

Bachelor of Computer Applications (BCA)

VCMT College of Management and Technology, Haldwani

2014 - 2017

Intermediate & High School

Govt Inter College Lohali

2012 - 2014

Get In Touch

I am currently seeking a leadership role to leverage my technical expertise, team collaboration, and DevOps skills. Whether you have a question or just want to connect, feel free to reach out!

Gurgaon, Haryana 8859859556
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