Praneetha K

About Praneetha K

I am a dynamic and motivated IT professional with 7 years of experience as a Big Data Engineer. I specialize in designing data-intensive applications using the Hadoop Ecosystem, Big Data Analytics, Cloud Data Engineering, Data Warehouse/Data Mart, and Data Quality solutions. I have extensive knowledge of Hadoop architecture and its components, including YARN, HDFS, MapReduce, Sqoop, Hive, HBase, Oozie, Flume, Kafka, and Spark. I excel in data ingestion, processing, and transformation using tools like Sqoop, Flume, Hive, and MapReduce. I have experience in Oozie workflow scheduling and implementing security with Kerberos authentication. In addition, I am proficient in designing and optimizing data storage in Hive using concepts like partitions and bucketing. I have hands-on experience with AWS services, including EC2, S3, RDS, and EMR. I am skilled in database management with SQL and NoSQL databases like MongoDB and HBase. I have expertise in ETL workflows, CI/CD pipelines, and automation tools like GIT, Terraform, and Ansible. My skill set extends to dimensional modeling, RDBMS design, web development using Python, Django, and frontend technologies. I am experienced in machine learning, predictive modeling, and statistical analysis using Python packages such as pandas, numpy, sci-kit-learn, and matplotlib. I am a highly skilled Big Data Engineer with expertise in Hadoop, data processing, cloud engineering, and database management.

Experience

1. Sr Aws Data Engineer

   Syntax

   Dec 2022 — Present · NC, US

   Architected and designed the overall AWS infrastructure for migrating and optimizing mission-critical applications, ensuring scalability, performance, and security. • Responsible for architecting, designing, and implementing scalable and efficient AWS infrastructure solutions for data processing, storage, and analytics. • Developed migration strategies and implemented seamless application migration to AWS, utilizing services like AWS Glue, EMR, Lambda, and Spark for data processing and transformation. • Optimized data pipelines and ensured data quality and integrity throughout the migration process, leveraging tools like AWS EMR and Spark SQL for efficient data movement and computation. • Fine-tuned AWS infrastructure components, including EC2 instances, Auto Scaling, and Load Balancing, to optimize performance, cost-efficiency, and resource utilization. • Developed and implemented data processing workflows and transformations using AWS services like AWS Glue, EMR to meet evolving business needs. • Conducted Data blending, Data preparation using Alteryx and SQL for Tableau consumption, and publishing data sources to the Tableau server. • Developed Kibana Dashboards based on the log stash data and integrated different source and target systems into Elastic search for near real-time log analysis of monitoring end-to-end transactions. • Monitored the performance and availability of migrated applications, proactively troubleshoot issues, and conducted end-to-end architecture and implementation assessments of AWS services like EMR, Redshift, and S3. • Continuously optimizing and fine-tuning the AWS infrastructure to enhance performance, cost-efficiency, and security. • Implemented AWS Step functions to automate and orchestrate the Amazon Sage Maker-related tasks such as publishing data to S3, training the ML model, and deploying it for prediction. • Integrated Apache Airflow with AWS to monitor multi-stage ML workflows with the tasks running on Amazon Sage Maker.

Education

• Amrita Vishwa Vidyapeetham

  Electronics and Computer Engineering

  2022 — 2026