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Prashanth Kandhada

@prashanthkandhada

Data Engineer at Wells Fargo building financial data pipelines and real-time fraud decisioning systems.

At Wells Fargo, I engineer PySpark and Delta Lake pipelines on AWS EMR for daily financial transaction data, reducing batch latency by 34%. I also built serverless streaming pipelines that feed credit-risk and fraud decisioning systems.

I previously developed distributed data platforms at LTIMindtree, including an Apache Flink and Kafka streaming platform and an Apache Iceberg lakehouse on Azure Data Lake Storage Gen2. My work improved processing times, downstream responsiveness, and storage costs.

At Hexaware Technologies, I created ETL frameworks on Azure Databricks and Apache Spark and developed Informatica PowerCenter pipelines for retail data. I also built an Enterprise Data Lakehouse & RAG Intelligence Platform with validation and observability workflows.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Wells Fargo

Nov 2024 - Present (1 year 11 months)

Engineered PySpark and Delta Lake pipelines on AWS EMR to ingest and transform 2TB+ of daily financial transaction data, cutting batch latency by 34%. Orchestrated ingestion from 25+ upstream systems and built modular dbt transformation layers on Snowflake and Redshift.

PySpark Delta Lake Amazon EMR Apache NiFi Fivetran DBT Snowflake Amazon Redshift AWS Lambda DynamoDB TensorFlow PySpark MLlib GitHub Actions AWS CodePipeline Snowflake Tasks DataOps CI CD

Data Engineer

LTIMindtree

Apr 2021 - Jul 2023 (2 years 3 months)

Developed distributed ETL pipelines in PySpark and Spark SQL to process 1.2TB+ of daily transactional and telemetry data, reducing pipeline execution time by 31%. Architected an event-driven streaming platform on Apache Flink, Kafka, and Zookeeper, and implemented a lakehouse on Apache Iceberg over Azure Data Lake Storage Gen2.

PySpark Spark SQL Apache Flink Kafka ZooKeeper Apache Iceberg Data Lake Storage Gen2 Azure Data Factory Airflow Snowflake Azure SQL Talend ETL Data Lakehouse

Associate Data Engineer

Hexaware Technologies

May 2019 - Mar 2021 (1 year 10 months)

Created large-scale ETL frameworks on Azure Databricks and Apache Spark processing 1TB+ of transactional and customer data daily, improving pipeline performance by 28%. Implemented ingestion and curation workflows across Azure Data Lake Storage Gen2 and Snowflake, and developed Informatica PowerCenter ETL pipelines consolidating 2TB+ of data from 300+ retail outlets.