Chandana J
Data Engineer @Deloitte
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WORK HISTORY
Data Engineer @Deloitte
Hyderabad, IN
Engineered distributed data processing pipelines using PySpark on AWS EMR, ensuring reliable data delivery to critical systems• Designed and implemented end-to-end ETL/ELT workflows to support ingestion, transformation of data for 65+ applications.• Developed and optimized robust Airflow DAGs to manage batch investment data flows, reducing retry resolution latency by 20%• Collaborated and automated Source-to-Target Mappings for interfaces minimizing data transformation errors• Developed a cutting-edge GenAI-powered data mapping tool using Python, Transformers, LLMs, reducing manual mapping effort by 60% and improving mapping accuracy• Enhanced operations and deployment workflows by implementing GitHub Actions, Docker.• Engineered and deployed a production-ready RFP Accelerator, a Retrieval-Augmented Generation (RAG) pipeline, reducing proposal review time and effort by 30%
EDUCATION
Indian Institute of Technology, Hyderabad
Bachelor of Technology - BTech
Indian Institute of Technology Hyderabad
Bachelor's degree
ABOUT CHANDANA J
Transforming Businesses with Cloud-Native Generative AI Solutions As a highly motivated and AWS Certified Solutions Architect and AI Practitioner with 2.2 years of experience, I specialize in architecting and implementing scalable, distributed data platforms and cutting-edge Generative AI solutions in cloud-native environments. I am skilled in Python, AI/ML model development, managing workflows and orchestration with Apache Airflow workflow, PySpark, SQL, Langchain and a broad range of AWS services, including EMR, Lambda, S3, MWAA, EKS, Bedrock, and Opensearch. With a strong foundation in data engineering, I bridge the gap between traditional data pipelines and cutting-edge Generative AI (GenAI) applications. By leveraging my expertise in designing and deploying high-throughput ETL/ELT pipelines and managing complex data orchestration workflows, I enable the seamless integration of large-scale data processing and AI-driven insights. My data engineering expertise includes ETL/ELT pipelines orchestration, data modeling, data warehousing, data governance, and data quality frameworks. I am also experienced in microservice integration for scalable system design, container orchestration (Docker) for efficient deployment, and CI/CD pipelines (GitHub Actions) for automated testing and deployment. Dedicated to staying ahead of the curve in big data technologies and AI/ML innovations, I drive business value by solving complex challenges and uncovering new opportunities.
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