Swetha Chowdary

About Swetha Chowdary

IT Professional with a strong background in end-to-end enterprise Data Warehousing and Data Engineering Projects. • Experience working with AWS cloud services i.e, S3 buckets, Cloud Watch, Redshift, Glue, Lambda, and EMR. • Experience in Migrating SQL databases to Azure Data Lake, Azure SQL Database, and Databricks. • Solid experience and understanding of designing and operationalizing large-scale data and analytics solutions on Snowflake Data Warehouse. • Experience in Designing end-to-end scalable architecture to solve business problems using various Azure Components like Data Factory, and Data Lake. • Domain Knowledge of Finance, Insurance, and Automotive Industries. • Developed, deployed, and managed event-driven and scheduled AWS Lambda functions to be triggered in response to events on various AWS sources including logging, monitoring, and security-related events, and to be invoked on a scheduled basis to take backups. • Good knowledge of integrating Spark Streaming with Kafka for real-time processing of streaming data and working knowledge of DBT on Azure cloud. • Experience in developing customized UDFs in Python. • Developed transformation logic using Snow Pipe. Hands-on experience working with snowflake utilities such as SnowSQL and SnowPipe. • Designed and implemented modular data models using dbt, optimizing transformations in cloud data warehouses such as Snowflake, Redshift, and Azure Synapse. • Integrated dbt with Databricks for large-scale data transformations, leveraging PySpark and SQL for efficient processing of structured and semi-structured data.

Experience

1. Sr Data Engineer

   Merkle

   Sep 2024 — Present

   Utilized Databricks and Apache Spark to process, clean, and transform over 2 billion records monthly before ingestion into Adobe Experience Platform (AEP), boosting pipeline performance by 45% and enabling near real-time data activation• Implemented cloud-based ingestion workflows leveraging AWS S3 and Adobe Landing Zones to enable seamless, scalable data exchange between source systems and AEP• Created and executed data models and ETL pipelines within the Adobe CDP (Customer Data Platform) environment to support advanced customer segmentation, targeting, and real-time personalization use cases• Structured schemas and data models in Adobe Experience Platform (AEP), enabling seamless data ingestion, identity resolution, and real-time customer profiling for personalized marketing• Built and optimized customer journeys in Adobe Journey Optimizer (AJO), leveraging audience segmentation, data queries, and real-time event triggers to drive targeted customer engagement across multiple channels• Configured seamless integrations between customer platforms (CRM, Martech, and ad tech) and CDPS to enable omnichannel experiences• Enhanced data architecture to improve data quality, availability, and monitoring, ensuring system interoperability and compliance with privacy requirements• Enforced identity resolution and profile collapse mechanisms to unify customer data across multiple sources.

Education

• University of North Texas

  Masters