Sai Settigari

About Sai Settigari

I am a Data Engineer with 3+ years of experience building scalable, cloud-native data solutions across AWS, Azure, and GCP. My expertise lies in designing and implementing end-to-end data pipelines, ETL/ELT frameworks, and analytics platforms that drive actionable business insights.At KPMG US, I design and optimize ETL processes, real-time streaming pipelines, and cloud migrations using Azure Data Factory, Databricks, Kafka, and Snowflake. Previously, at Procter & Gamble, I developed serverless pipelines with AWS Lambda, Glue, and Kinesis, modernizing legacy systems and delivering significant performance improvements. My earlier roles at Central Bank of India and Ajanta Pharma honed my skills in Big Data integration, workflow orchestration (Airflow/Composer), and multi-cloud data warehousing (BigQuery, Synapse, Redshift).I am highly skilled in Python, PySpark, SQL, and advanced Big Data technologies such as Spark, Hadoop, Kafka, and Delta Lake. Beyond data engineering, I bring strong knowledge in DevOps (Docker, Kubernetes, Terraform, Jenkins), machine learning pipelines, and data visualization with Power BI and Tableau.Certified in AWS, Azure, and GCP, I am passionate about building secure, efficient, and business-driven data ecosystems. My goal is to bridge data engineering with advanced analytics to empower organizations with reliable, future-ready insights.

Experience

1. Data Engineer

   Intercontinental Commodity Exchange

   Feb 2025 — Present · Atlanta, GA, US

   Designed and developed highly scalable ETL pipelines with Informatica to automate the ingestion of structured and semi-structured data into Snowflake, incorporating robust validation rules to maintain data quality and ensure alignment with Master Data Management (MDM) standards.Architected and implemented efficient data storage and processing solutions leveraging Microsoft Fabric, Azure Data Lake, Azure Synapse Analytics, and Azure SQL to enable decision-making across various business units at ICE.Led the end-to-end management of data warehouse solutions on Snowflake and Azure Synapse, from gathering business requirements to designing dimensional models, ensuring seamless and high-performance analytics.Implemented real-time data ingestion using Apache Kafka, enabling near-instantaneous data streaming and enhancing event-driven analytics to support timely decision-making and real-time operational insights.Enhanced query performance by 40% in Azure Synapse Analytics and Cosmos DB through the optimization of stored procedures, indexing strategies, and query execution plans, improving the performance of high-volume business intelligence (BI) applications.Developed a modern Delta Lake architecture on Databricks using Unity Catalog, applying Medallion Layering (Bronze, Silver, Gold) to ensure structured data organization, schema enforcement, and time-travel capabilities for seamless analytics and versioned data management.Managed the migration of on-premises Oracle and Teradata databases to Azure Data Lake Storage, ensuring minimal disruption and zero downtime during the cloud adoption process, while enhancing data access and enabling real-time analytics capabilities.Designed and optimized T-SQL stored procedures, functions, and views to support complex data transformation, reporting, and analytics tasks in both SQL Server and Azure Synapse, improving performance and maintaining data consistency across systems.

Education

• Rivier University

  Master's degree, Computer Science

• Teegala Krishna Reddy Engineering College

  Computer science , Computer Science