About

Kashika Jain is a Data Engineer II at American Family Insurance with over 5 years of experience in building data pipelines, data models, collecting and analyzing big-data & cloud (AWS/GCP) applications. She is proficient in working with cross-functional teams & non-technical business audiences while leading by decision-making. Kashika has a strong background in data engineering and has worked with various technologies such as Python, SQL, AWS, GCP, Amazon Athena, Apache Airflow, Spark, and more. Currently, Kashika is working as an iPhone/iPads Application Developer at Vertax Web Technology Private Limited. She has developed multiple IOS apps and social media websites for a US-based retail client. She has also collaborated with clients and internal teams to design application workflows and performed unit and QA testing. Previously, Kashika worked as a Senior Systems Engineer - Data Analyst at Infosys where she was a marketing analytics consultant for a leading retailer in the US. She was responsible for designing email marketing campaigns, A/B testing, and significance analysis. She evaluated the overall impact of campaigns by obtaining effectiveness metrics to compare incremental lift (Test vs Control) for activity, transactional, cost, and revenue metrics. Kashika also worked as a Data Science Intern at Autodesk where she outlined key sabbatical patterns of Autodesk employees to the Finance-Audit Team using Splunk's active directory data. She developed a predictive model for job retention and projected time series sabbatical trends. Kashika holds a Master's degree in Software Engineering from San Jose State University and a Bachelor of Technology in Information Technology from Poornima University. She has a strong tech stack that includes Data Engineering, SQL, AWS, Python, Amazon Athena, Apache Airflow, GCP, Sentiment Analysis, Recommendation system, Spark, Web, Salesforce, ETL, and Data Scientist. With 7.37 years of relevant experience, Kashika is a skilled data engineer who can effectively collaborate with cross-functional teams to build and maintain data pipelines, models, and applications.