About

Orpita Das is a highly skilled Data Engineer II at Snowflake, with a strong academic background in Molecular Biology and Biotechnology. She completed her Master of Science (M.Sc.) in Molecular Biology from the University of British Columbia and her Bachelor of Technology (B.Tech.) in Biotechnology from NIT Warangal. Orpita has over 7 years of relevant experience in the field of Data Engineering, with expertise in Snowflake, SQL, Python, ML, Javascript, NLP, test, XGBoost, Hyperparameter, Research Scientist, Neural Networks, Data Scientist, Keras, GCP, Seaborn, Spark, Pandas, MySQL, Flask, SVM, Deep Learning, Scikit, and Big Data. Orpita has a proven track record of developing modular, scalable object-oriented scripts with git version control, managing code environment, performing unit-testing, and running scripts in Bash shell. She is proficient in programming languages such as Python, R, C++, SQL, and Javascript and has worked with technologies like Snowflake, Tableau, Google Cloud Platform, and Bioinformatics tools & software. Orpita has also achieved top 13% in a Kaggle Machine learning competition. At Snowflake, Orpita is responsible for building and maintaining Data Ingestion and Automation pipelines for the organization, as well as supporting Snowflake Data Platform Operations activities using SQL/Javascript/Python. She has also trailblazed the implementation of Internal Audit SOX Exception Detection workflows that trigger Alerts as well as Analytics dashboards for use by Application control owners as well as the Internal Audit team. In her past roles, Orpita has worked as a Machine Learning Intern at the University of Waterloo and as a Data Scientist/Engineer at Lantern Institute. At the University of Waterloo, she developed a Python-based QSAR (Quantitative Structure-Activity Relationship) model for protein thermostability engineering while volunteering in Dr. Subha Kalyaanamoorthy's lab. At Lantern Institute, Orpita used Python libraries such as matplotlib, seaborn, plotly, numpy, pandas, datetime to clean & analyze Samsung Health device data. She also built a DASH app on GCP to display interactive visualizations of ‘effect of exercise/stress/day-time sleep’ on ‘night-time sleep’ for any selected time-range & aggregation type (daily/weekly/monthly). Orpita has also participated in several Kaggle competitions, including Credit Card Fraud Detection and Real or