I'm Namit Naik, a seasoned Big Data and AWS professional with a proven track record of
delivering complex data solutions to meet business needs. My expertise in these
technologies has allowed me to help organizations unlock the full potential of their
data, leading to improved decision making and business outcomes.
With extensive experience in cloud computing, I have designed and implemented AWS-based
Big Data solutions using services such as S3, EMR, EC2, Lambda, Step-Function, Glue &
Redshift. I have a deep understanding of programming languages such as Python and SQL,
as well as Big Data processing frameworks like Apache Spark and Apache Hive.
I am dedicated to staying up-to-date with the latest industry advancements and expanding
my skillset. I possess excellent problem-solving skills, effective communication
abilities, and a strong team mentality.
Made significant contributions to a successful Proof of Concept (POC) that involved transitioning ETL framework from AWS EMR and Informatica to AWS Glue. My roles included setting up the AWS Glue environment, designing an end-to-end job pipeline, addressing data challenges, and developing CI/CD code. Also provided training, collaborated on test automation, and played a key role in converting test suites from Pandas to PySpark. Additionally, helped to implement a unified HTML Test Automation report and concluded the POC by migrating Test-Automation Suite to an AWS EMR cluster.
Tasks involving cleaning and refining data, setting up data streaming using Kafka and connecting it to S3, creating visual data displays with Tableau, and maintaining written records and documentation.
Grade: 80%
Responsible for maintaining PySpark scripts, which involved error detection and correction to ensure the proper processing of raw data. Developed a PySpark tool, known as JSON-Hive, that utilized dynamic Data Definition Language (DDL) to store JSON data in HIVE tables. Created PySpark scripts for transforming flattened data into JSON format and contributed to building an AWS Step Functions pipeline for triggering Informatica (BDM) workflows. Integrated the JSON-Hive Spark utility into existing pipeline and identified an optimization approach for EMR Cluster utilization based on the size of incoming JSON files landing on AWS S3 Bucket.
CGPA: 9.24/10
Grade: 90%
In the study undertaken, we have created a chatbot in education domain & it is named as “College Enquiry Chatbot”. This chatbot is a web-based application that analyses and understands user's queries and provides an instant and accurate response.
In the study undertaken, we reviewed several papers & discussed types of chatbots, their advantages & disadvantages. The review suggested that chatbots can be used everywhere because of its accuracy, lack of dependability on human resources & 24x7 accessibility.
This article usually briefs on:
-What actually Mixed Reality is ???
-Its evolution with Microsoft HoloLens 2
-What can we do with MR ???
-Why it has an edge over Virtual Reality ???
If you are in need of a highly experienced Big Data and AWS professional to take your data initiatives to the next level, feel free to reach out. I would love to discuss how I can bring my expertise to your organization and drive positive results.
Mumbai MH, India 421201