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💻 Anand Satheesh

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Software Architect at IBM India
Big Data Enthusiast | Data Engineering Specialist | Microservices Architect


🚀 About Me

Hello! I'm Anand Satheesh, a seasoned software architect with over 11 years of experience in building robust big data and data engineering solutions. Currently, I am working at IBM India, where I leverage my expertise to architect and implement scalable data pipelines, data lakes, and microservices architectures.


🛠️ My Skill Set

Big Data Technologies:

  • Apache Spark: Proficient in both PySpark and Scala
  • Kafka: Real-time data streaming and processing
  • Hadoop: Distributed storage and processing

Data Engineering:

  • Data Lakes: Building and managing large-scale data lakes
  • Data Warehousing: Designing efficient and scalable data warehouses
  • ETL Pipelines: Developing end-to-end ETL workflows

Microservices:

  • Architecture: Designing and implementing microservices-based systems
  • Containerization: Docker, Kubernetes for deploying scalable applications
  • APIs: Creating and managing RESTful APIs

Programming Languages:

  • Python: Data processing, scripting, automation
  • Scala: Big data processing with Apache Spark
  • Java: Backend development

Cloud Platforms:

  • IBM Cloud: Cloud-native solutions and services
  • AWS: Data engineering and cloud services

📚 Latest Blog Posts


📫 Let's Connect


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Anand Satheesh's Projects

airflow icon airflow

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

airflow_sensors icon airflow_sensors

A project to test various possibilities with airflow sensors, the file sensor is tested here which will listen for a file delivery at a specific location and trigger a workflow based on the condition if the file is received or not

billionrowsstreaming icon billionrowsstreaming

A program to utilize apache spark and kafka to process a stream of a billion recording in real time. An attempt inspired by the billion record challenge, this project attempt to use distributed processing capacity of apache spark to process a billion rows that can be process as a stream from a source

books_project icon books_project

This repository contains a set of microservices designed using Fast api package in python

brew icon brew

🍺 The missing package manager for macOS (or Linux)

couchdb icon couchdb

Seamless multi-master syncing database with an intuitive HTTP/JSON API, designed for reliability

dbt-core icon dbt-core

dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.

debezium icon debezium

Change data capture for a variety of databases. Please log issues at https://issues.redhat.com/browse/DBZ.

delta icon delta

An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs

fastapi icon fastapi

FastAPI framework, high performance, easy to learn, fast to code, ready for production

flask icon flask

The Python micro framework for building web applications.

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