Sai Thondapu
Data Engineer @TD
Signup · Get unlimited contacts
WORK HISTORY
Data Engineer @TD
Toronto, ON, CA
Developed Python scripts for data extraction, transformation, and loading, automating data workflows with Azure Data Factory to reduce manual intervention.• Used Azure Event Hubs for real-time data streaming and processing, allowing quick analysis of data for important business decisions. • Optimised SQL queries using window functions and stored procedures, transformed data with DAX expressions, and built monitoring Power BI dashboards on Azure to improve data quality and support better decision-making.• Accelerated large-scale data processing using Databricks and parallel computing techniques, processing datasets exceeding 50TB• Identified and validated data between source and target applications, ensuring data consistency and accuracy. • Created and improved database schemas and data models in Azure SQL and Synapse Analytics, using indexes and query tuning to make data access up to 3x faster. • Improved data processing speed using Databricks performance tuning techniques like partitioning, caching, and parallel processing, supporting efficient risk management for real-time and batch processing.• Set up monitoring and logging in CI/CD pipelines using Azure DevOps to quickly detect and resolve deployment issues. • Developed and maintained detailed documentation of notebooks, ETL workflows, and data ingestion processes in Confluence, ensuring compliance with best practices.• Collaborated with cross-functional teams and DevOps teams to ensure continuous integration and continuous deployment data pipelines on Azure.
EDUCATION
Gayatri Vidya Parishad College of Engineering (Autonomous)
Bachelor's degree
Northeastern University
Master of Science - MS
ABOUT SAI THONDAPU
Staying relevant has never been more important in these fast-changing times. My career journey has been an evolving path of continuous learning and growth. From my early days as an engineering student writing small programs to transitioning into Data Engineering, I have gained diverse experiences that have shaped my expertise. With 6 years of hands-on experience in Data Engineering, I specialize in end-to-end ETL processes, data pipeline development, reporting, and analysis. I have designed and built scalable data pipelines capable of handling vast amounts of data in both batch and real-time environments. Passionate about taking ownership, I thrive on collaborating with business teams and stakeholders to deliver impactful data-driven solutions. This collaborative approach has not only enriched my professional journey but has also deepened my passion for data engineering. My toolkit is a blend of various tools and technologies, including but not limited to: Hadoop Ecosystem (HDFS, Hive) Scala / Python Spark (PySpark, Databricks) Snowflake SQL (SQL Server, Oracle, MySQL) Tableau, Power BI Azure Cloud (ADF, ADLS/Blob, Synapse, and other related services) Machine Learning: Predictive Analytics, Classification, Fine Tuning Key Competencies: Pipeline Building | ETL Optimization | Performance Tuning | Data Warehousing | Data Modeling | Data Visualization | Data Governance & Data Security | Data Lineage & Metadata Management | Release Management | Testing & Debugging | Stakeholder Management | Communication | Problem-Solving | Mentorship Beyond my professional experience, my Master’s in Information Systems strengthened my knowledge of data, allowing me to explore machine learning algorithms, visualize complex datasets, and even build ML pipelines from scratch. Additionally, serving as a Teaching Assistant allowed me to break down complex database design concepts for peers, making abstract ideas more accessible through workshops and discussions. This experience reinforced my passion for knowledge sharing, as I find great fulfillment in helping others understand and apply technical concepts effectively. I strongly believe in continuous learning and enjoy exploring emerging technologies, pushing myself beyond my comfort zone. What excites me most about this field is its ever-evolving nature—there’s always a new challenge to tackle, a new tool to master, and new opportunities to create value from data.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.