Vivek Ananda

About Vivek Ananda

As a Data Engineer at NYL GBS, I design and implement scalable data solutions using…

Experience

1. Data Engineer

   Citi

   Mar 2024 — Present · Dallas, TX, US

   Designed, developed, and maintained end-to-end operations of ETL data pipelines using Azure Data Factory and Databricks, ensuring efficient data extraction, transformation, and loading processes. Developed custom activities using Azure Functions, Databricks, and PowerShell scripts to perform data transformations, cleaning, and validation. Ingested data into Azure Services (Azure Data Lake, Azure Storage, Azure SQL) and processed it within Databricks for enhanced analytics. Ingested datasets from diverse sources including flat files, CSV, RDBMS, FTP, and XML, applying data mapping, cleansing, and normalization to enhance data quality and consistency. Developed data validation frameworks to ensure accuracy and consistency of data across various financial reports, improving compliance and reporting integrity. Designed and maintained scalable data models for the Enterprise Data Warehouse (EDW), optimizing analytical workloads following Kimball Dimensional Modeling best practices. Developed batch and near-real-time ETL/ELT pipelines using Databricks and PySpark, improving data ingestion efficiency by 40%. Automated CI/CD deployment of ETL pipelines using GitHub Actions and Azure DevOps, reducing deployment time by 50%. Optimized Airflow DAGs for scheduling and orchestrating complex data workflows across Azure infrastructure, enhancing operational efficiency. Collaborated with cross-functional teams to implement BI solutions using Power BI, ensuring seamless data accessibility and insightful reporting. Enhanced data governance and security through robust data integrity validation and automated anomaly detection processes. Developed and fine-tuned large language models (LLMs) for use cases such as natural language processing and text generation, improving user interactions and task automation. Implemented machine learning-based anomaly detection for transactional data, reducing false positives in fraud detection by 25%.

Education

• University of Bridgeport

  Master's degree, Computer Science