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💫 About Me:

🔭 An experienced backend engineer with a strong focus on delivering high-quality products. With six years of hands-on experience, I have a deep understanding of defining requirements, designing, implementing, testing, and delivering complex back-end and web applications. My skill set includes:


- ▪ Programming Languages: JavaScript, Python, TypeScript
- ▪ Methodologies: Microservice Architecture, Serverless, Agile, XP, Pair-programming, Test-driven Development
- ▪ Tools and Technologies: AWS, Elasticsearch, Terraform, Pulumi, Kubernetes, Docker, REST, Web3, Spark, Kafka, Camunda
- ▪ Databases: MySQL, Cassandra, DynamoDB, MongoDB, PostgreSQL
- ▪ Frameworks: Node.js, Express.js, Flask, React.js, Nest.js, Django

💬 I thrive in creating scalable architectures and have a passion for solving complex problems. With a keen attention to detail, I ensure that every aspect of the product is crafted meticulously. I believe in collaborating closely with cross-functional teams to achieve remarkable results.

🌱 If you are looking for a dedicated engineer who can bring technical excellence and a product-centric mindset to your team, let's connect and explore potential opportunities.

💻 Tech Stack:

JavaScript Python Solidity TypeScript NodeJS Express.js FlaskReact React Router Redux NestJs AWS Lambda EC2 RDS SES DynamoDB SQS API Gateway S3 ElasticSearch Docker Kibana Kubernetes Kafka Apache Spark Pulumi Terraform MongoDB MySQL Postgres Redis RabbitMQ MQTT Cassandra CSS3 HTML5 Vercel Jest Mocha Chai Sequelize Socket.io Django pytest SQLAlchemy JWT pandas Storybook Bootstrap Chart.js MUI GraphQL Webpack NPM Yarn LINUX Bash Ubuntu ESLint Swagger Jira Notion Agile/SAFe Scrum GIT Bitbucket Web3 Camunda sonarqube

🌐 Socials:

LinkedIn Twitter

Dhananjay Patil's Projects

autocomplete icon autocomplete

basic autocomplete in Node.js using trie data structure

cl1 icon cl1

CL-I Practical Exam SPPU

cnn icon cnn

Digit Recognition using Convolutional Neural Network done on MNIST dataset. Accuracy of 97.33% was obtained using this ConvNet model. Python Libraries used: {Pandas, Keras, Tensorflow}

cnn-js icon cnn-js

Digit Recognition using CNN with TensorFlow.js

register icon register

Grab your own sweet-looking '.is-a.dev' subdomain.

tic-tac-toe icon tic-tac-toe

The application was developed in Qt Creator as part of project for SPPU CGG Lab of Semester 4 (2015-16)

youtube-downloader icon youtube-downloader

https://www.npmjs.com/package/ytdl-core - Yet another youtube downloading module. Written with only Javascript and a node-friendly streaming interface.

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