Bhargav Mardimani

About Bhargav Mardimani

Highly experienced Data Infrastructure Engineer with 10 years in Platform Engineering and Data Engineering roles, specializing in high-volume, low-latency data intensive applications and systems. Proven success in managing and scaling distributed systems, automating operational tasks, and building robust CI/CD pipelines for data and ML environments and leading teams. Adept at troubleshooting critical production systems and collaborating with cross-functional teams.As a Data Engineer at Amazon, I am passionate about data and work on finding and leveraging the right data patterns to generate useful business insights, and run machine learning workflows - considering the volume, variety, velocity, and value of the data. I have extensive experience in using AWS Data Platform tools, such as RDS, Redshift, EMR, S3, Glue, Lambda, Athena, DynamoDB, Kinesis, and MWAA to build scalable, reliable, and secure data pipelines and solutions serving the OLAP, OLTP and Science workloads. I graduated with a Master\'s degree in Computer Science from Illinois Institute of Technology specializing in Databases, where I won the Innovative Idea Award by Amadeus for developing a web application that helps travelers pack efficiently based on the weather and location of their destination. I also have a Bachelor of Engineering in Instrumentation Technology from R. V. College of Engineering, Bangalore, where I published a paper on the comparative analysis of existing pulse oximeters in the global market. I am proficient in SQL, Python, Spark, AWS, and I love using Jupyter notebook to create narrative and interactive data stories.

Experience

1. Senior Data Engineer - Amazon Fulfillment Technologies Ai

   Amazon

   Aug 2024 — Present · Bellevue, WA, US

   Designed and implemented a comprehensive AFT AI Data Platform: Leveraged AWS S3, Redshift, Apache Airflow, and AWS Glue to build a unified data foundation. This initiative reduced dataset subscription time by 95%, improved query performance by 82%, and established automated deployments, significantly enhancing real-time analytics capabilities and data preparation for the ML lifecycle.Developed a robust Data Ingestion Framework and Processing System: Created an ETL framework capable of handling structured, semi-structured, and unstructured data formats, drastically reducing the time to build new data ingestion pipelines from weeks to hours.Led end‑to‑end design and implementation of an MCP‑based data platform that unified training and inference data, cutting metric onboarding time from 3 days to under 3 hours (≈96% reduction).Led the design of Integration with LLMs and AI assistants, achieving 40% faster documentation creation and 60% reduction in code review cycles while establishing best practices for the team.Led implementation of AI-assisted code generation and review process for pipeline configurations, reducing manual coding errors by 35%.Transformed operational intelligence by automating technical documentation and architectural diagrams generation, resulting in 50% faster incident response times and creation of comprehensive onboarding materials that reduced new hire ramp-up by 2 weeks.

Education

• RV College Of Engineering

  Bachelor of Engineering (B.E.), Instrumentation Technology

  2010 — 2014

• St. Aloysius (Deemed to be University)

  Pre-University, Physics, Chemistry, Math and Biology

• Illinois Institute of Technology

  Master’s Degree, Computer Science

  2016 — 2018

Skills

• R
• Git
• Hive
• Windows
• Prezi
• Public Speaking
• Matlab
• Microsoft Powerpoint
• Sql
• Amazon Web Services (Aws)
• Teamwork
• Mongodb
• Hadoop
• Apache Kafka
• C++
• Powerpoint
• Microsoft Excel
• Weblogic
• Microsoft Word
• Hbase
• Apache Pig
• Data Analysis
• Cassandra
• Java
• Sqoop
• C
• Programming
• Python
• Html
• Tomcat
• Apache Spark
• Web Applications
• Microsoft Office