About memy skills
Information About me
I am an optimistic person and am always prepared to put in the effort in any circumstance. I am passionate about pursuing a challenging and fulfilling career with a legitimate company that acknowledges my true potential while enhancing my analytical as
well as technical expertise. I am highly flexible and adaptable when it comes to work on different projects.
Work experience
Company: Informatica Business Solutions Private Limited, Bengaluru
Job Role: Associate Data Automation Engineer (Started as Data Automation Intern; converted to full-time in Sept 2024)
Duration: Sept 2023 – Present
Started as a Data Automation Intern at Informatica, where I implemented automated monitoring and alerting systems for Data Integration (DI) jobs using Python, shell scripting, and scheduling tools, enabling proactive failure detection and reducing manual intervention through intelligent email notifications. I optimized data pipeline performance by restructuring jobs to run in parallel, stabilizing job dependencies, and validating execution consistency using historical success logs. Additionally, I troubleshot recurring job failures by analyzing system logs, minimizing precision-related issues, and fine-tuning configurations to enhance runtime efficiency and job reliability. Following my conversion to a full-time Associate Data Automation Engineer, I led the migration of data ingestion pipelines from Java to Python, utilizing Parquet file formats on Amazon S3 to load data into OpenSearch—improving system observability, monitoring, and reducing operational overhead. I developed Superset dashboards to visualize customer adoption metrics and identify potential leads from usage data, enabling targeted outreach by internal teams and improving customer retention while lowering acquisition costs. Furthermore, I migrated jobs to Datashare sources with PDO enabled to accelerate performance, and transitioned from traditional Secure Agent deployments to a serverless architecture, eliminating AMI-based agent migrations and enhancing deployment scalability and cost efficiency.
Education
2019 - 2024
Integrated MTech CSE in Business Analytics - Vellore Institute of Technology
CGPA - 9.13
2017 - 2019
Senior Secondary (MPC) - Sri Chaitanya Junior College
class Xll
96.7%
2016 - 2017
Secondary High School - Krishnaveni High School
class X
GPA - 9.3
volunteering
2022 - 2023
Director of Finance - Uddeshya of VIT
Managing financial operations, making strategic financial decisions, and providing financial guidance to the executive team.
2022 - 2023
Director of Events - Uddeshya of VIT
Involves planning, coordinating, and executing various types of events, such as conferences, meetings.
2021 - 2022
Content team Member - Game Development Club of VIT
Responsible for creating and managing the club's content.
My ProjectsMy Work
Here is some of my projects that I've done in the College.
Desktop Personal Assistant (DORA)
As soon as the user provides speech as input, it is transformed to text, after which the input is examined and mapped to a certain function.
My Portfolio
Designed and developed a personal portfolio website using HTML, CSS, and JavaScript to showcase my skills, experience, and projects.
Music genre classification
Music audio is converted to a spectrogram, which is then fine-tuned using a combinational approach, and a classification model is trained to predict the genre label.
Road Sign Recognition
I have developed a comprehensive approach that effectively detects and recognizes traffic signs by employing techniques for image preprocessing, as well as employing methods for sign detection, recognition, and categorization.
Student Performance Prediction
This is the Flask application of Student Performance Prediction where we use Machine Learning Algorithm to predicts Students performance based on the data given.
Bookmyshow Scrapper
Taking movie name and city name as input from UI it will fetch the theater name and show details which are available in the theater and total gross collection of the theater and total booked gross of each show .
Disease Prediction and Drug Recommendation
Taking symptoms as input to predict the disease and recommends the drug based on the data extracted from twitter.
Facebook Data Analysis
Data from Facebook was scraped, and the runtimes of Spark and Python ML algorithms were compared. The retrieved data was then subjected to sentiment analysis and data visualisation.
Contact MeContact
Explore my profiles
Write to me