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@rahul31agrawal
rahul31agrawal
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Rahul Agrawal rahul31agrawal

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rahul31agrawal/README.md

Hello there! 👋
I’m a passionateData Engineer with expertise in designing and implementing scalable data solutions. I work across multiple platforms and tools to transform raw data into actionable insights that drive decision-making and innovation.


🛠️Tech Stack & Skills

Programming & Scripting

  • SQL: Proficient in writing complex queries, optimizing performance, and designing relational database structures.
    SQL
  • Python: Expertise in scripting, automation, and data manipulation using libraries like Pandas, NumPy, and Matplotlib.
    Python

Big Data & ETL Tools

  • Apache Spark: Skilled in distributed data processing, optimizing transformations, and handling massive datasets.
    Apache Spark
  • PySpark: Specialized in DataFrame operations, performance tuning, and advanced analytics on Spark.
    PySpark
  • Apache Airflow: Orchestrating complex workflows and ensuring robust ETL pipelines.
    Airflow

Cloud Platforms

  • Azure: Extensive experience in Azure Data Factory, Databricks, and cloud-based data engineering workflows.
    Azure
  • AWS: Building scalable and resilient architectures with AWS S3, Glue, and Lambda.
    AWS

Data Engineering & Storage

  • Databricks: Expertise in building and optimizing big data pipelines for real-time processing and analytics.
    Databricks
  • Data Warehouse: Proficient in designing and managing data warehouses for seamless querying and reporting.
    Data Warehouse

CI/CD & DevOps

  • Docker: Containerizing applications and ensuring consistency across environments.
    Docker
  • GitHub: Managing version control and collaborating effectively across teams.
    GitHub

Visualization & Analytics

  • Power BI: Designing interactive dashboards and reports to visualize complex datasets.
    Power BI
  • Microsoft Fabric: Exploring new frontiers in data visualization and analytics.
    Microsoft Fabric

🌟What I Do

End-to-End Data Engineering: Architecting and implementing robust data pipelines for ETL processes.
Cloud Integration: Leveraging Azure and AWS for scalable and efficient data workflows.
Big Data Solutions: Managing massive datasets and optimizing performance using Spark and PySpark.
Data Visualization: Crafting insightful dashboards and reports with Power BI and Microsoft Fabric.


🚀Current Focus Areas

  • 🏗️ MasteringMicrosoft Fabric andData Mesh Architectures.
  • 🌐 Exploringmulti-cloud integrations and hybrid architectures.
  • 📈 Enhancing skills inData Warehousing andBI Tools.

👨‍💻Let’s build the future of data together!

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