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SreejaYerramsetti/README.md

Hi, I'm Sreeja 👋

Data Engineer with experience building ETL/ELT pipelines and cloud-native data platforms across fintech, healthcare, and retail. I work primarily with Python, SQL, PySpark, Azure Databricks, and AWS — and I've been diving into Generative AI (LangChain, RAG, LLMs) to build smarter data tooling.

Currently exploring: applied NLP and GenAI-powered data applications.

🔧 What I work with

  • Languages: Python, SQL, PySpark
  • Data Engineering: ETL/ELT, Lakehouse Architecture, Delta Lake, Data Modeling
  • Cloud: Azure (Databricks, ADF, ADLS Gen2), AWS (Glue, EMR, Redshift, S3)
  • GenAI: LangChain, RAG, Azure OpenAI, Prompt Engineering
  • Visualization: Power BI, Streamlit

📌 Projects

EchoMood — Music Sentiment Analysis Pipeline An NLP pipeline that analyzes sentiment in online music discussions using VADER, TextBlob, and TF-IDF, with a Faktory-based job queue, PostgreSQL storage, and a Streamlit dashboard.

📫 Reach me

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  1. echomood-music-sentiment-nlp echomood-music-sentiment-nlp Public

    NLP-powered sentiment analysis pipeline for music discussions using VADER, TextBlob, TF-IDF, Faktory, PostgreSQL, and Streamlit.

    Python