Tejendra Etla

Data Engineer i @Doublene Technology LLC

Los Angeles, CA, US
MOBILE NUMBERS
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WORK HISTORY

Oct 2023 — Present

Data Engineer i @Doublene Technology LLC

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Developed and optimized ETL pipelines using Python, SQL, and PySpark, processing large datasets using Apache Nifi to enhance data accessibilityand reduce processing time by 30%.• Designed and deployed comprehensive data warehousing solutions on AWS Redshift and Google BigQuery, achieving real-time analyticscapabilities that reduced reporting delays by 40%, enhancing decision-making processes.• Implemented scalable data warehousing and analytics solutions in Snowflake, optimizing query performance and enabling seamless integrationwith BI tools for faster insights.• Supported machine learning initiatives using Scikit-Learn and TensorFlow, preparing clean datasets that enhanced model accuracy by 35%.• Automated data workflows using Apache Airflow and AWS Step Functions, increasing pipeline efficiency and reducing manual work by 50%.• Built and maintained data models for Tableau and Power BI, providing actionable insights that improved decision-making processes and reducedanalysis time by 25%.• Leveraged Docker and Kubernetes for containerization and orchestration, streamlining deployment processes and decreasing setup time by 20%.

EDUCATION

N/A

California State University, Northridge

Master of Science - MS, Computer Science

N/A

Vellore Institute of Technology

Bachelor's degree, Electronics and Communications Engineering

ABOUT TEJENDRA ETLA

Data Engineer with strong experience building scalable, reliable data platforms in healthcare and enterprise environments. I specialize in lakehouse and streaming architectures using Spark, Kafka, Snowflake, dbt, and Airflow, delivering measurable impact such as faster data freshness, higher pipeline reliability, and reduced compute costs. I focus on clean data modeling, performance optimization, and data quality to enable trusted self-service analytics, while mentoring teams and driving engineering best practices across the data platform.

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