Raghavendra B

Data Scientist · Data Engineer · ETL/ELT Developer

Bengaluru, Karnataka, India

@raghavendra_b

0 followers

About

Data professional with hands-on experience building data pipelines, ETL/ELT workflows, and analytical dashboards using Python, SQL, Spark, Airflow, Kafka, and cloud data platforms. Focused on data quality, reproducibility, and reliable pipeline delivery across structured and unstructured data.

Experience

Data Science Intern

Excelr

Jul 2025 – Jan 2026

Designed and maintained automated data pipelines to support large-scale data processing; developed and optimized data ingestion and transformation workflows; built reusable ML pipelines for preprocessing, feature engineering, model training, and evaluation; collaborated to troubleshoot pipeline issues and validate data integrity.
Data Analysis Intern

TekkyBench

Dec 2024 – Jan 2025

Performed data ingestion, cleaning, and transformation on raw structured datasets using Python and SQL; applied data validation and quality checks; built interactive Power BI and Tableau dashboards for stakeholder reporting.

Education

Bachelor of Computer Application

Government First Grade College, Sagara

Computer Application · Sep 2022 – Jul 2025

Skills

6 to 12 months

NumPy Python Pandas Data Ingestion Data Engineering Model Evaluation Feature Engineering

<3 months

SQL ETL Bash Streamlit TensorFlow scikit-learn Apache Spark Data Quality Data Modeling Data Integrity Data Governance NoSQL Databases Data Processing Data Warehousing Distributed Systems

Tools / apps / platforms

6 to 12 months

Git GitHub

<3 months

MySQL Docker MongoDB Tableau Snowflake Terraform Kubernetes PostgreSQL Apache Kafka Apache Hadoop Apache Airflow Microsoft Power BI Google Cloud Platform Amazon Web Services AWS

Projects

Apple Stock Price Prediction ↗

Python, Time Series, Data Pipeline, Streamlit

Preprocessed, transformed, and validated historical stock market data; trained and evaluated a SARIMA model to predict future prices; built an interactive Streamlit web app to visualize historical trends and forecasted results.
Customer Shopping Behavior Analysis ↗

Python, SQL, ETL, Power BI, Streamlit

Designed SQL-based data extraction and transformation workflows; performed data validation and quality checks; built Power BI dashboards and a real-time Streamlit application to visualize sales trends and customer behavior insights.
Swiggy Delivery Time Prediction ↗

Python, MLOps, DVC, Data Pipeline, Streamlit

Built a reproducible data processing and ML pipeline covering data ingestion, transformation, feature engineering, and model evaluation; applied data validation and quality checks; deployed the model with Streamlit and used DVC for data version control and pipeline reproducibility.
Apple Stock Price Prediction ↗

Python, Time Series, Data Pipeline, Streamlit

Preprocessed, transformed, and validated historical stock market data; trained and evaluated a SARIMA model to predict future prices; built an interactive Streamlit web app to visualize historical trends and forecasted results.
Customer Shopping Behavior Analysis ↗

Python, SQL, ETL, Power BI, Streamlit

Designed SQL-based data extraction and transformation workflows; performed data validation and quality checks; built Power BI dashboards and a real-time Streamlit application to visualize sales trends and customer behavior insights.
Apple Stock Price Prediction ↗

Python, Time Series, Data Pipeline, Streamlit

Preprocessed, transformed, and validated historical stock market data; trained and evaluated a SARIMA model to predict future prices; built an interactive Streamlit web app to visualize historical trends and forecasted results.
Customer Shopping Behavior Analysis ↗

Python, SQL, ETL, Power BI, Streamlit

Designed SQL-based data extraction and transformation workflows; performed data validation and quality checks; built Power BI dashboards and a real-time Streamlit application to visualize sales trends and customer behavior insights.
Swiggy Delivery Time Prediction ↗

Python, MLOps, DVC, Data Pipeline, Streamlit

Built a reproducible data processing and ML pipeline covering data ingestion, transformation, feature engineering, and model evaluation; applied data validation and quality checks; deployed the model with Streamlit and used DVC for data version control and pipeline reproducibility.

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