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Developer Advocate @Snowflake | Data & AI engineering
📌 "In God we trust; all others must bring data." Data & AI practitioner with a unique blend of data engineering, machine learning, artificial intelligence and business analysis expertise. Currently, as a Developer advocate at Snowflake I work on Data Engineering and AI workloads. In my professional experience, I have worked on end-to-end data & AI projects that involved Data Engineering, Data Modeling, Machine Learning Model Deployment, Data Visualization, and Analytics Framework Development for solving business problems. Most recently, as a Data Engineer at Applied ML Search team at Apple, I built a search metrics data store for retail/e-commerce data, and developed automated training pipelines for search query intent classification model and learn-to-rank ML models in production. Previously, as an AI Engineer at IproTech, I worked on a custom NLP model for Named Entity Recognition that identifies and redacts personally identifiable and sensitive information from unstructured text documents. Prior to that, I worked as a Data Engineer at Nike creating robust and scalable enterprise data pipelines for the Consumer Data Analytics & Engineering (CDEA) team. ✅ Programming: Python (Numpy, Pandas, NLTK, Spacy, Scikit-Learn), PySpark, SQL. ✅ Big Data Tools & Frameworks: Apache Spark, Snowflake, Hadoop, ETL data pipelines, Apache Airflow, Hive, AWS (EMR, S3, EC2, Lambda, SNS, Glue, Redshift), lakeFS ✅ VCS, DevOps & Misc Tools: PyCharm, VS Code, Git, Jira, Jenkins, Docker ✅ Statistics: Inferential Statistics, Experimental Design, Hypothesis Testing (A/B Testing), Regression Analysis ✅ Machine Learning: Regression Modeling, Random Forest, XGBoost, kNN Classifier, K-means Clustering, Feature Extraction (PCA, Factor Analysis), Natural Language Processing (Text Analytics – PII, PHI Extraction), Convolutional Neural Network. ✅ Business Domain Expe
PSG College of Technology
B.E., Electronics and Communications Engineering
N/A – Present
W. P. Carey School of Business – Arizona State University
Master of Science - MS, Business Analytics
N/A – Present
Snowflake
Senior Developer Advocate - Data & AI Engineering
August 1, 2025 – Present
Snowflake
Developer Advocate - Data & AI Engineering
July 1, 2023 – August 1, 2025
Treeverse - the lakeFS creators
Developer Advocate - Data Engineering, Machine Learning, MLOps
May 1, 2022 – June 1, 2023
San Francisco Bay Area
Apple
Data Engineer - Applied AI & Search
April 1, 2021 – May 1, 2022
Sunnyvale, California, United States
Nike
Data Engineer Co-op
August 1, 2020 – October 1, 2020
Remote
Arizona State University
Explainable AI Researcher
September 1, 2019 – May 1, 2020
Tempe, Arizona, United States
IPRO
AI Engineer - Language Models (NLP)
August 1, 2019 – March 1, 2021
United States
NetApp
Software Engineer II - Customer Success Ops
April 1, 2017 – May 1, 2018
Young Leaders for Active Citizenship (YLAC)
Research Analyst - Public Policy
February 1, 2017 – March 1, 2017
Bangalore
Indian Institute of Technology, Bombay
Open Source Contributor, Scilab Textbook Companion Project
December 1, 2015 – January 1, 2016
Mumbai
NetApp
Software Engineer I - Customer Success Ops
August 1, 2015 – April 1, 2017
NetApp
Software Engineer Intern
December 1, 2014 – July 1, 2015
Caterpillar Inc.
Business Intelligence Analyst
May 1, 2014 – June 1, 2014
Greater Chennai Area
Research: Explainable AI (XAI) - Uncovering what is under the black box models
December 1, 2019 – May 1, 2020
- Built a simple Convolutional Neural Network for hand-written image recognition with MNIST dataset. - Visualized the CNN filters and maxpool blocks at every layer, plotting model weights and activation values in fully-connected layers corresponding to different inputs. - Using activation maximization to understand which neuron in the model gets activated by which abstract feature of the input image, to generalize the neuron activations. Mentor: Dr. Asim Roy, Professor, Department of Information Systems, W.P.Carey School of Business. Programming Language: Python (Keras)
Statistical Design of Experiments
November 1, 2019 – December 1, 2019
- Objective was to design and build a Lego car using Design of Experiment and Lean Six Sigma design principles that achieve optimal performance in terms of the distance traveled. - Conceptualized and designed a half-fractional factorial experiment with 7 different factors and conducted experimental trials to identify optimal levels of the input factors to achieve better performance. Tools Used: MiniTab, MS Excel
Regression Analysis - Factors affecting the IQ of a person
November 1, 2019 – December 1, 2019
- Studied different factors that affect the IQ of human beings and built a regression model to understand the impact of each factor. - Factors like country of origin, annual income of the household and number of years of school education turned out to he statistically significant factors and the regression had an R-square of 68%. - Conclusion of the study is that remaining 32% of the variability in IQ of a person is not explained by the factors analyzed. Tools Used: MS Excel (StatTools Plugin)
Analytical Decision Modeling at Chik-Fil-A outlet
October 1, 2019 – December 1, 2019
- Modeled and automated the employee scheduling process at a Chik-Fil-A outlet in Arizona State University campus. - Increased the flexibility of the employee schedule by automating it using Excel solver plugin thereby reducing manual intervention and thus increasing productivity of the store supervisor as well. Tools Used: MS Excel (Solver Plug-in)
Optimizing Tempe Bus Timetable under Time Dependent Demand
October 1, 2019 – May 1, 2020
- Performed Exploratory Data Analysis in python to understand the existing peak hour demand and the Orbit bus schedule in different routes. - Analyzing stochastic demands and cumulative wait times of passengers at bus stops to design a demand-responsive and congestion-sensitive timetable thus reducing the overall wait times of all passengers. - Defining and measuring customer satisfaction metrics of the Orbit bus system to identify scope of improvements and provide data-driven recommendations to the Tempe Department of Transportation. Programming Language: Python (Pandas, NumPy, MatplotLib, Seaborn), MS Excel (Solver, @Risk Plugins)
Kaggle: Classifying dissatisfied customers of Santander Bank using different classification algorithms
October 1, 2019 – October 1, 2019
- Explored and understood different classification algorithms like Decision tree classifier, Random Forest Classifier, AdaBoost classifier, Gradient Boosting Classifier and XGBoost Classifier to improve AUC and achieved a Kaggle score of 0.67 for the given data set. - Used SMOTE module to tackle the imbalanced class problem as the training set had 96% satisfied customers and 4% dissatisfied customers. Programming Language: Python (Scikit-learn, Imbalanced-learn, Pandas, Numpy, MatplotLib, Seaborn)
Analyzing most successful Movies, Directors and Production houses by worldwide collections
September 1, 2019 – September 1, 2019
- Created Tableau Dashboards to understand the most successful movies, directors and production houses by worldwide revenue. - Inferred how different genres of movies were successful in different decades and how different production houses rose to prominence in the last decade in the Hollywood industry. Tools Used: MS Excel, Tableau
Scilab Textbook Companion Project
January 1, 2016 – Present
Successfully completed the Internship under Scilab Textbook Companion for a duration equivalent to six weeks. I have coded, in Scilab, all the solved examples of the allotted textbook: Signals And Systems by V. Krishnaveni And A. Rajeswari. This work was funded by the FOSSEE (Free and Open Source Software for Education) project, IIT Bombay. Mentor: Dr.V.Krishnaveni, Associate professor, PSG College of Technology, Coimbatore Programming language: Scilab (An open-source equivalent of Matlab)
RFID based valuables safety system
December 1, 2013 – Present
Designed a prototype of a smart home where RFID tags are embedded on the valuable items such as Credit cards, Jewelries, etc. When any of these items are stolen from the house, the RFID reader at the doorstep reads the RFID tag of the object being stolen and sends the signal to the microcontroller AT89S52 which turns ON the buzzer as an indication of theft. Programming Language: Assembly C
FIRST Tech Challenge 2014: FTC Block Party - Design and Implementation of Autonomous pick and place robot
December 1, 2013 – March 1, 2014
Designed, built and programmed (using Robot C ) a robot to autonomously pick and place the plastic bricks in crates. - Designed a LegoNXT Robotics kit - Awarded best design - Programming language: RobotC Achievements: Won the FTC Inspire Award and FTC winning alliance award and bagged an opportunity to do summer internship at Caterpillar India Pvt. Ltd.,
Automatic accident detection via embedded GSM message & call interface
June 1, 2013 – Present
Designed an accident detection module that uses a piezoelectric sensor to detect the vibrations on a vehicle body during a crash. The piezo sensor sends a signal to the AT89C52 microcontroller, that inturn uses GSM to call and send message to Police/Ambulance for emergency rescue. Programming Language: Assembly C
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from embedded systems to advanced ML research and public policy, demonstrates a broad intellectual curiosity and adaptability. Their experience in both large corporations (Apple, Nike, Snowflake) and open-source communities (lakeFS, IIT Bombay) suggests an ability to thrive in various organizational cultures. The target role of ML Engineer aligns well with their recent professional trajectory and academic background in Business Analytics, indicating a strong interest in data-driven problem-solving.
Soft Skills & Operational Fit
The candidate's experience in Developer Advocacy roles suggests strong communication and collaboration skills, which are beneficial for cross-functional teams. Their research background indicates a proactive and analytical approach to problem-solving. The project descriptions highlight an ability to work independently and deliver tangible results.