Chamanthi Pyneni
Data Engineer | Python, SQL, AWS, Airflow, Snowflake, Spark | ETL & Data Pipelines | 3+ YOE | Fintech & Healthcare
- Role
- Data Engineer at Fifth Third Bank
- Location
- Houston, TX, US
- LinkedIn followers
- 500 followers
About Chamanthi Pyneni
Most organizations don’t struggle with data.They struggle with reliable data pipelines.That’s the problem I enjoy solving.I’m a Data Engineer with 3+ years of experience building scalable ETL pipelines and cloud data platforms using Python, SQL, AWS, Snowflake, Apache Airflow, and Spark.My work focuses on transforming raw data into reliable, analytics-ready datasets that power dashboards, reporting, and machine learning systems.At Fifth Third Bank, I optimized Snowflake workloads and improved query performance by 35%, reducing latency and compute costs.I enjoy building data systems that scale, remain observable, and run reliably in production.Tech Stack:Python | SQL | AWS | Snowflake | Apache Airflow | Spark | ETL | Data Pipelines | Data Warehousing | Data Lake | Data Engineering
Experience
Data Engineer
Jun 2024 — Present · Kentwood, MI, US
Working on an Enterprise Customer Insights & Credit Analytics Platform supporting large-scale banking data analytics.Key Contributions• Built and maintained scalable ETL pipelines using Python and Apache Airflow, ingesting data from Oracle, Salesforce, and internal banking systems into Snowflake and AWS Redshift, processing 15M+ records daily.• Designed cloud data lake architecture (AWS S3 → Glue → Redshift) enabling centralized storage and analytics for customer insights and credit risk reporting.• Developed data transformation workflows using Python, Pandas, PySpark, and SQLAlchemy to process structured and semi-structured financial datasets.• Implemented data quality validation using Great Expectations, improving pipeline reliability and data accuracy.• Optimized Snowflake SQL workloads and query performance, reducing query latency by 35% and improving analytics efficiency.• Built CI/CD pipelines with Jenkins and GitHub Actions to automate ETL deployment and improve release reliability.• Implemented data lineage and metadata tracking using AWS Glue Data Catalog to support governance and compliance (SOX, PCI-DSS).Tech Stack:Python, SQL, AWS (S3, Glue, Lambda, Redshift), Snowflake, Apache Airflow, PySpark, Jenkins, Power BI
Education
University of Central Missouri
Master of Science - MS, Computer Science
Vasireddy Venkatadri International Technological University
Bachelor of Technology - BTech, Computer Science
2019 — 2023
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