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grandhi02/README.md

💫 About Me:

As a data engineer, I specialize in designing and implementing scalable solutions for data-driven challenges. My professional interests lie in data analytics, operations and data warehouse, where I want to integrate data engineering expertise with emerging technologies.

With hands-on experience in PySpark, SQL, and Airflow, I develop robust data pipelines and analytics frameworks. My technical toolkit also includes MLflow for model tracking, Kubernetes for container orchestration, Jenkins for CI/CD, and Hive and Kafka for managing big data ecosystems.

I'm skilled in Python programming and leverage tools to optimize workflows and enable efficient data storage and retrieval. Driven by curiosity, I’m constantly exploring innovations in DevOps and latest technologies to deliver cutting-edge solutions.

🌐 Socials:

LinkedIn Medium email

💻 Tech Stack:

Debezium Kubernetes Apache Iceberg Data Warehouse Python Apache Spark Apache Kafka Apache Hive Jenkins Apache Airflow Apache Superset MySQL Neo4J mlflow Matplotlib NumPy Pandas Git GitHub MCP

✍️ Dev Quote

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  1. Change-Data-Capture-with-Debezium Change-Data-Capture-with-Debezium Public

    Change Data Capture using Debezium with data quality

    Python 1

  2. Spark Spark Public

    The Dataframe APIs and the Spark documentation

    Jupyter Notebook 1

  3. airflow airflow Public

    airflow

    Python

  4. Recurrent-Neural-Network-for-Stock-Price-Trends Recurrent-Neural-Network-for-Stock-Price-Trends Public

    Using LSTM to remove vanishing gradient descent for finding Trends

    Jupyter Notebook 1

  5. Streamlit-for-Cardiac-predicton Streamlit-for-Cardiac-predicton Public

    Python 1 2

  6. HPEEzmeral/aie-tutorials HPEEzmeral/aie-tutorials Public

    AIE Engineering managed demo tutorials for AI Essentials on PCAI

    Jupyter Notebook 5 5