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👋 Hi there, I'm Manohar!

I'm a passionate Data Engineer specializing in building scalable data pipelines, data warehousing, and analytics solutions. With a strong background in data science and engineering, I enjoy tackling complex data challenges and leveraging data to drive business insights.

🌱 About Me

  • Recently completed a Master of Science in Data Science at Indiana University.
  • Over 2 years of experience in data engineering, focusing on building and optimizing data pipelines using AWS, GCP, and Snowflake.
  • Proficient in programming languages such as Python, Java, and SQL, with hands-on experience in big data analytics like PySpark, Kafka and in visualization tools like Tableau and Power BI.
  • Enthusiastic about emerging technologies, machine learning, and Gen AI.

💼 Professional Experience

  • Data Engineer: Developed and maintained data pipelines with Docker and Airflow for processing and analyzing text data and metadata from book files.
  • Data Analytics Engineer: Conducted research and integrated diverse data sources at the O'Neil School of Public and Environmental Affairs, significantly improving data accuracy and retrieval speed.
  • Associate Data Engineer: Worked at Accenture, focusing on HR and Payroll data, enhancing operational efficiency through innovative data solutions.

🔧 Skills

  • Languages: Python, Java, SQL, R, C
  • Tools & Technologies: Docker, Airflow, AWS, Snowflake, Tableau, Power BI, Neo4j, ChatHuggingface
  • Concepts: Data Engineering, Data Warehousing, ETL, Data Modeling, Machine Learning

📂 Projects

  • Reddit Data Engineering Pipeline: Led the development of a robust data pipeline using Apache Airflow, Docker, and AWS, extracting data with Python and PRAW API for improved efficiency.
  • Financial Data Streaming Pipeline: Built a data ingestion pipeline using Docker, Kafka, and Spark, optimizing real-time data processing for financial analytics.
  • Real-Time Food Delivery Data Analytics: Developed a data processing pipeline using AWS Kinesis and PySpark Streaming, enhancing analysis capabilities through a QuickSight dashboard.
  • CRNY Survey Data Analysis: Analyzed survey data to explore guaranteed income's impact on artistic communities in New York, providing insights into demographics, enrollment, financial wellness, and COVID-19 effects.
  • Global Football Transfer Market Analysis: Conducted a comprehensive analysis of the football transfer market across the top 5 global leagues, examining financial trends and player transfer dynamics.

📫 Connect with Me

Feel free to reach out or connect with me on LinkedIn or through email at [email protected].

Thanks for visiting my GitHub profile! 🌟

Naga Manohar Yelubandi's Projects

airline_data_ingestion icon airline_data_ingestion

An end-to-end data ingestion pipeline for airline data, utilizing various AWS services to process and store flight information efficiently.

crny_survey_data_analysis icon crny_survey_data_analysis

Explore how guaranteed income impacts New York's diverse artist community, revealing insights into financial resilience and societal support through interactive Power-BI dashboard.

e_comerce icon e_comerce

Django E-comerce Application deploying on AWS

pyspark_sales_data_analysis icon pyspark_sales_data_analysis

Unlock hidden insights in your sales data with PySpark! Explore customer spending patterns, product popularity, and sales trends to drive better business decisions.

reddit-pipeline-de icon reddit-pipeline-de

Explore the world of Data Engineering through a sophisticated ETL pipeline leveraging Reddit's API, AWS S3, Redshift, dbt transformations, and Airflow orchestration in Docker. Visualize insights on r/dataengineering with a dynamic Google Data Studio report, showcasing the power of integrated data tools in action.

tensorflow icon tensorflow

Project containig related material for my TensorFlow articles

travel-weather icon travel-weather

A Python HTTP API to demonstrate Codespaces working with Copilot

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