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baratamavinash225/README.md

Hey there 👋, I'm Avinash

Senior Data Engineer | Backend Engineer | GCP | Big Data | ML & GenAI

🚀 About Me

  • 💼 11.5+ years of experience in Data Engineering, Backend Development & Machine Learning
  • ☁️ Strong focus on Cloud (GCP, AWS, Azure) and scalable data platforms
  • 🔄 Expertise in building end-to-end data pipelines (batch & streaming)
  • 🧠 Experience in ML pipelines, NLP, and data-driven systems
  • 🏗️ Passionate about designing production-grade, scalable architectures
  • ⚡ Focus on performance, cost optimization, and data reliability

🏢 Current Focus

  • Building GCP-based data platforms using BigQuery, Dataproc & Composer
  • Developing data observability & auditing systems (usage tracking, cost insights)
  • Designing backend APIs & microservices for data systems
  • Working on streaming + batch architectures (Lambda/Kappa)

☁️ Cloud & Data Platforms

Google Cloud (Primary)

  • BigQuery, GCS, Dataproc, Cloud Composer (Airflow), Pub/Sub
  • Vertex AI (ML workflows & pipelines)

AWS

  • S3, SNS, SQS, EventBridge, EMR, EKS

Azure

  • ADLS, ADF, Databricks, Synapse

⚙️ Data Engineering Stack

  • Big Data: Spark, Hadoop, Hive, Kafka, Kafka Connect, NiFi
  • Processing: Batch & Streaming (Lambda Architecture)
  • Orchestration: Airflow, Cloud Composer, Oozie, Dolphin Scheduler
  • Data Stores: BigQuery, PostgreSQL, MySQL, Oracle, HBase
  • Pipelines: ETL / ELT, Data Warehousing, Data Lakes

🖥️ Programming & Backend

  • Backend: Spring Boot, Microservices, REST APIs
  • Languages: Python, Java, Scala
  • System Design: Scalable distributed systems

🧠 ML, NLP & GenAI

  • Feature Engineering & Data Preparation
  • NLP-based systems (Entity Resolution, Text Processing)
  • Supervised & Unsupervised Learning
  • Deep Learning & Neural Networks
  • MLOps & pipeline integration
  • Exploring LLMs, embeddings, and GenAI workflows

🛠️ DevOps & Infrastructure

  • Docker, Kubernetes
  • CI/CD (Jenkins, GitOps)
  • Ansible, Rundeck
  • Linux, Shell scripting
  • Secure systems with Vault

📊 Key Strengths

  • ✅ Designing scalable data platforms
  • ✅ Building reliable data pipelines (TB-scale)
  • ✅ Optimizing BigQuery cost & performance
  • ✅ Developing backend systems for data applications
  • ✅ Enabling data governance & observability

📌 Highlight Projects

  • 🔐 Secure Secret Management (Vault + Kafka Connect)
  • 📊 BigQuery Usage Audit Platform (Data Observability & FinOps)
  • 🧠 Entity Resolution using NLP for Corporate Clients

📫 Let's Connect

⭐️ Always open to collaborating on Data Engineering, Cloud, and AI-driven projects

Popular repositories Loading

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    Seek Answers and solutions

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  4. Python_yaml_merge Python_yaml_merge Public

    This is to merge 2 yaml configurations and create a superset of the yaml file from the two configurations

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    This application is to integrate spring boot with the prometheus. Simple use case is to generate a metrics on prometheus as how many requests has hit to the spring boot application

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