• 📈 5+ years of working experience in building scalable data-pipeline for ingesting and analyzing large scale datasets using Big Data framework.
• 🌱 I'm on track for learning more about Data Engineering, Systems Design, Cloud Architecture and Machine Learning Pipelines.
• 🎯 I am keen to develop products that impact on a large scale. 𝙄 𝙖𝙢 𝙘𝙪𝙧𝙧𝙚𝙣𝙩𝙡𝙮 𝙡𝙤𝙤𝙠𝙞𝙣𝙜 𝙛𝙤𝙧 𝙁𝙪𝙡𝙡-𝙏𝙞𝙢𝙚 𝙟𝙤𝙗 𝙤𝙥𝙥𝙤𝙧𝙩𝙪𝙣𝙞𝙩𝙞𝙚𝙨 𝙖𝙣𝙙 𝙄 𝙖𝙢 𝙞𝙣𝙩𝙚𝙧𝙚𝙨𝙩𝙚𝙙 𝙞𝙣 𝘿𝙖𝙩𝙖 𝙀𝙣𝙜𝙞𝙣𝙚𝙚𝙧𝙞𝙣𝙜 𝙖𝙣𝙙 𝘿𝙖𝙩𝙖 𝙎𝙘𝙞𝙚𝙣𝙘𝙚 𝙧𝙤𝙡𝙚𝙨
• ✍️ In my free time, I go out to explore new places or stay in to write journals.
• 💬 Feel free to reach out to me for pro bono consulting and volunteering, or just for some interesting discussion.
• 📫 How to reach me: by mail, or LinkedIn
• 😄 Pronouns: He/Him

🛠 Tech Stack

• ► Programming Languages: Python, PySpark, SQL, shell-scripting.
• ► Databases: MySQL, PostgreSQL, MongoDB (NoSQL), Cassandra, Amazon Redshift.
• ► Machine Learning: Classification, Regression, Clustering, Neural Networks, Ensemble Learning, Forecasting, Dimension Reduction, Predictive modeling, CNN, GAN.
• ► Libraries: Asyncio, Pandas, Numpy, Scikit-learn, NLTK, Requests, Matplotlib, Tensorflow, Keras, Beautiful Soup, Selenium.
• ► Framework/Tools: Apache Spark, Spark Streaming, Hadoop, HBase, Hive, Nifi, Apache Kafka, Apache Airflow, Tableau, Git, GitHub, Bash, MS Excel, IntelliJ, Jupyter Notebooks, Flask, FASTAPI.
• ► DevOps Tools: Docker, Kubernetes.
• ► Cloud Technologies: Amazon Web Service (AWS), Google Cloud Platform (GCP).