Pravallika Modugu

Experience

1. Data Engineer

   Capital One

   Sep 2024 — Present · US

   Engineered and deployed real-time, event-driven data pipelines using Apache Kafka, Spark Structured Streaming, and Apache Airflow on both AWS and Azure, enabling ingestion of 25M+ daily customer, payment, and fraud events into Snowflake and Azure Synapse, supporting credit risk scoring and fraud analytics with sub-minute latency.Modernized legacy batch ETL pipelines by migrating to Databricks on Azure Data Lake Storage Gen2 and Delta Lake, implementing ACID-compliant streaming ingestion frameworks using PySpark, reducing data latency by 50% and pipeline failures by 70%.Integrated internal APIs, S3, Azure Blob Storage, and third-party data vendors using AWS Glue, Azure Data Factory, and Lambda Functions, automating ingestion and transformation workflows across hybrid cloud environments.Designed high-performance data models and analytical layers in Snowflake and Synapse, implementing clustering keys, dynamic partitioning, and materialized views to optimize analytical queries across dashboards used by finance, credit policy, and compliance teams.Implemented Confluent Schema Registry and Kafka Connect for schema versioning and connector management, ensuring compatibility and stability across producer-consumer pipelines in a multi-team ecosystem.Led data governance initiatives using Apache Atlas, Azure Purview, and Great Expectations to establish lineage, anomaly detection, role-based access, and compliance tracking (SOX, GDPR), ensuring enterprise-grade data quality and audit readiness.Automated CI/CD for infrastructure and data pipelines using Terraform, Azure DevOps, GitHub Actions, and AWS CodePipeline, enabling blue/green deployments, rollback support, and version-controlled infrastructure-as-code (IaC).

Education

• University at Buffalo

  Master's degree, Data Science

• G. Narayanamma Institute Of Technology And Science

  Bachelor of Technology - BTech, Electronics and communication