Sai Charan Reddy

AI/ML Data Engineer @ Wells Fargo

About

I am a Data Engineer with 6+ years of experience building scalable data platforms, high-performance ETL pipelines, and modern cloud data architectures that power enterprise analytics and business intelligence. My work focuses on transforming complex raw data into reliable, analytics-ready datasets that enable organizations to make faster, data-driven decisions. I specialize in designing end-to-end data pipelines using Azure Data Factory, PySpark, SQL, and distributed data processing frameworks. I have extensive experience integrating large volumes of data from APIs, relational databases, and cloud storage into modern data warehouses such as Snowflake, Redshift, and Azure Synapse. By implementing optimized partitioning strategies, incremental loading, query tuning, and scalable pipeline orchestration, I have consistently reduced data latency, improved pipeline performance, and increased data availability for enterprise reporting and analytics teams. Throughout my career, I have worked closely with business stakeholders, data scientists, analysts, and engineering teams to design reliable data architectures that support large-scale analytics, regulatory reporting, and machine learning workloads. I focus strongly on data quality, governance, and performance optimization to ensure data platforms remain scalable, secure, and production-ready. My technical expertise includes cloud data engineering, distributed data processing with Spark and Databricks, ETL/ELT pipeline development, data warehousing, and building high-impact dashboards using Power BI and Tableau. I enjoy solving complex data challenges, optimizing large-scale data systems, and enabling organizations to unlock the full value of their data. Let’s connect if you’re hiring for Data Engineering or AI/ML roles — I bring proven experience in building secure, scalable, and performance-optimized data systems.

Country

United States

City

Dallas

Industry

Computer Software

Skill

Microsoft Azure, Microsoft Excel, Pyhton, Extract, Transform, Load (ETL), SQL, Transact-SQL (T-SQL), U.S. Health Insurance Portability and Accountability Act (HIPAA), power BI, Snowflake , Python (Programming Language), PySpark, Snowflake, Amazon Web Services (AWS), Kafka

Experience

AI/ML Data Engineer

Wells Fargo

2025-2 - 2026-2 · 1 yr 1 mo

Optimized Azure Data Factory ETL pipelines using Mapping Data Flows and partitioned data processing, reducing data pipeline latency by 38% and improving daily batch processing SLAs. • Redesigned SQL Server transformation logic and indexing strategies, reducing query execution time by 45% for high-volume financial transaction datasets. • Implemented incremental data loading and change data capture (CDC) strategies in Azure pipelines, reducing data ingestion latency by 40% and minimizing full table refresh operations. • Worked closely with business stakeholders, data analysts, and risk teams to translate reporting requirements into scalable ETL workflows and data models.

Data Engineer

Sentara Health

2023-9 - 2024-10 · 1 yr 2 mos

Developed business-rule-driven transformations using PySpark and SQL, improving data accuracy by 30%. Optimized ETL workflows through indexing, query tuning, and Spark partitioning, cutting batch processing time by 40%. Designed Snowflake schema data models for analytics-ready healthcare datasets. Developed Power BI and Tableau dashboards tracking patient outcomes, lab trends, and operational KPIs. Led legacy system data migrations with validation and reconciliation, ensuring zero business disruption. Optimized Azure Data Factory ETL pipelines using Mapping Data Flows and partitioned data processing, reducing data pipeline latency by 38% and improving daily batch processing SLAs. • Redesigned SQL Server transformation logic and indexing strategies, reducing query execution time by 45% for high-volume financial transaction datasets. • Implemented incremental data loading and change data capture (CDC) strategies in Azure pipelines, reducing data ingestion latency by 40% and minimizing full table refresh operations. • Worked closely with business stakeholders, data analysts, and risk teams to translate reporting requirements into scalable ETL workflows and data models. Worked closely with clinicians and analysts to deliver secure, reliable, and scalable data solutions

Software Engineer

QVANTEL SOFTWARE SOLUTIONS LIMITED

2020-2 - 2022-5 · 2 yrs 4 mos

Hyderabad, Telangana, India

Developed scalable PySpark and SQL data pipelines processing high-volume batch datasets. Improved data processing latency by 25% through pipeline optimization. Implemented Kafka + Spark Streaming for near real-time analytics use cases. Supported ML model development and deployment using Scikit-learn and TensorFlow, reducing deployment time by 20%. Applied data quality checks using Great Expectations, improving dataset reliability by 20%. Built analytics datasets and supported Power BI/Tableau dashboards, increasing reporting adoption by 30%. Collaborated with cross-functional teams to deliver data and ML solutions aligned with business needs.

Data Analyst

GNR IT Solutions

2019-6 - 2019-12 · 7 mos

Supported business requirement analysis and data validation activities. Wrote SQL queries for reporting and ad-hoc analysis. Created Power BI dashboards to visualize trends and KPIs. Used Excel (Pivot Tables, formulas) for data cleaning and analysis. Gained hands-on exposure to Agile/Scrum data project workflows.