I am Sai Sindhura Pappala, an Experienced Senior Data Engineer with over 8 years of proven success in designing, building, and optimizing large-scale data pipelines and analytical solutions. I have deep experience with cloud-based architectures, particularly AWS Redshift, and Big Data technologies such as Hadoop, Spark, and Hive. I am adept at leveraging Python for data ingestion, transformation, and automation, focusing on scalable, efficient, and reliable data workflows. I am skilled in implementing best practices for data modeling, ETL/ELT development, and performance tuning to support critical business intelligence and machine learning initiatives. I am passionate about driving data-driven decision-making and continuously evolving modern data platforms to meet growing enterprise needs.

Sai Sindhura Pappala

I am Sai Sindhura Pappala, an Experienced Senior Data Engineer with over 8 years of proven success in designing, building, and optimizing large-scale data pipelines and analytical solutions. I have deep experience with cloud-based architectures, particularly AWS Redshift, and Big Data technologies such as Hadoop, Spark, and Hive. I am adept at leveraging Python for data ingestion, transformation, and automation, focusing on scalable, efficient, and reliable data workflows. I am skilled in implementing best practices for data modeling, ETL/ELT development, and performance tuning to support critical business intelligence and machine learning initiatives. I am passionate about driving data-driven decision-making and continuously evolving modern data platforms to meet growing enterprise needs.

Available to hire

I am Sai Sindhura Pappala, an Experienced Senior Data Engineer with over 8 years of proven success in designing, building, and optimizing large-scale data pipelines and analytical solutions. I have deep experience with cloud-based architectures, particularly AWS Redshift, and Big Data technologies such as Hadoop, Spark, and Hive. I am adept at leveraging Python for data ingestion, transformation, and automation, focusing on scalable, efficient, and reliable data workflows.

I am skilled in implementing best practices for data modeling, ETL/ELT development, and performance tuning to support critical business intelligence and machine learning initiatives. I am passionate about driving data-driven decision-making and continuously evolving modern data platforms to meet growing enterprise needs.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
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Work Experience

Career Break
November 1, 2023 - November 22, 2025
Relocated to Australia and dedicated time to caring for a young child; provided consulting on data engineering solutions during the transition and prepared for ongoing work in the Australian market.
Data Engineer at Tyfone Solutions (Former Cubus Banking Solutions)
October 1, 2023 - October 1, 2023
Designed and implemented a lightweight ETL framework to ingest and transform data from multiple sources, storing it in HDFS and Hive tables with dynamic DDL generation for external tables. Built Spark-based batch pipelines for data cleaning, transformation, and aggregation, and performed performance tuning on Spark jobs. Worked with Hadoop ecosystem (HDFS, Hive) to manage raw and processed data, and authored Python scripts for extraction, transformation, and loading within the data lake environment. Optimized file formats and partitioning (Parquet, ORC) to enhance Athena/Query performance and collaborated with senior engineers for troubleshooting and documentation.
Senior Data Engineer at Tyfone Solutions (Former Cubus Banking Solutions)
October 1, 2023 - October 1, 2023
Designed and developed an automated ETL framework using Python to extract, transform, and load structured and semi-structured data into Amazon S3 data lake. Built streaming frameworks using Spark and Kafka (Confluent) for real-time ingestion, created dynamic metadata-driven ETL pipelines with AWS Glue, and built Athena tables dynamically with DDL scripting to accommodate schema evolution and optimized data formats (Parquet, ORC). Implemented reusable Python modules for data validation, error logging, and notifications. Developed scalable ETL pipelines feeding Amazon Redshift for reporting and analytics, and integrated with Airflow for orchestration and monitoring. Optimized S3 partitioning strategies for improved query performance.

Education

Bachelor's degree in Computer Science and Engineering at Vishnu Institute of Technology
January 1, 2010 - January 1, 2014

Qualifications

AWS Certified Cloud Practitioner
January 11, 2030 - November 22, 2025
AWS Certified Data Engineer - Associate
January 11, 2030 - November 22, 2025

Industry Experience

Financial Services, Software & Internet