Summary
Work History
Education
Skills
Languages
Education Certifications
Disclaimer
Timeline
Generic

Dayanand Shettar

Hubballi

Summary

Dynamic data professional with a proven track record at [Previous Employer], excelling in ETL pipeline development and data processing using PySpark. Adept at leveraging AWS tools and Apache Airflow for orchestration, I thrive in collaborative environments, driving impactful data solutions that enhance decision-making and operational efficiency.

Work History

Data Engineer

  • Optimized enterprise data warehouse performance and improved query efficiency through schema redesign and ETL enhancements.
  • Conducted in-depth analysis of existing warehouse schema and identified bottlenecks in query performance.
  • Re-engineered data models and normalized schema structures to reduce redundancy and improve scalability.
  • Implemented efficient partitioning, bucketing, and indexing strategies in Spark SQL, reducing query execution time by 30-40%.
  • Refactored ETL pipelines using PySpark to handle large-scale data loads with improved fault tolerance.
  • Collaborated with analysts and business users to ensure optimized data accessibility for reporting and dashboards.

Data Engineer

  • Designed and deployed a scalable, end-to-end data pipeline to forecast customer churn and provide actionable insights.
  • Built automated ingestion pipelines with AWS Lambda to capture and preprocess streaming customer interaction data.
  • Designed a PySpark-based workflow for feature engineering, transformation, and model training on historical customer datasets.
  • Integrated machine learning models with Spark MLlib/Pandas for churn prediction, improving accuracy and reducing false positives.
  • Automated deployment of prediction results into AWS Redshift, enabling real-time reporting and visualization through BI tools.
  • Partnered with business stakeholders to translate predictive outputs into retention strategies, driving customer satisfaction and reducing churn by X%.
  • Technologies: Python, PySpark, AWS (Lambda, Redshift, S3), Pandas

Education

B.Tech - Computer Science

KLE Society's KLE Institute of Technolgy
Hubballi
08-2020

Master of Science - Data Science

Kingston University London
Kingston Upon Thames
09-2022

Skills

  • Python and SQL
  • Data processing with PySpark
  • Apache Spark and Pandas
  • ETL pipeline development
  • Amazon Web Services (AWS) tools
  • Apache Airflow orchestration
  • Version control with Git
  • Jupyter Notebook usage
  • Visual Studio proficiency

Languages

  • English
  • Kannada
  • Hindi

Education Certifications

Machine Learning, SQL, Data Analysis - Dataquest

Disclaimer

I hereby declare that all information furnished by me is true to best of my knowledge.

Timeline

Data Engineer

Data Engineer

B.Tech - Computer Science

KLE Society's KLE Institute of Technolgy

Master of Science - Data Science

Kingston University London

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Dayanand Shettar