New Grad@ December 2023 | Full Time Data Engineer
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am a graduate student currently pursuing a Master's degree in Computer Science at San Jose State University, California, with a strong focus on data engineering (December 2023 graduate). I am deeply passionate about solving problems and have developed a keen interest in this field. My expertise in data structures and extensive experience with big data technologies have greatly enhanced my skills as a data engineer.
Over the course of my six-year career in India, I have had the privilege of working with renowned companies such as Macquarie Bank, IHS Markit, and Apple, where I have sharpened my abilities as a data engineer. Working both independently and collaboratively, I have gained valuable skills in leadership and teamwork.
My proficiency lies in Java, Python, SQL, and NoSQL databases, big data technologies (Apache MapReduce, Apache Spark, Apache Pig, Hive), Cloud (AWS, GCP), backend development(REST API), and Machine Learning algorithms. I am always eager to learn new technologies and continually improve my skill set as I shape my career.
During my graduate program at San Jose State University, I have delved into a range of courses, including Machine Learning, Cloud Computing, Design and Analysis of Algorithms, Web Search-Information retrieval, DB systems, NoSQL systems, Database principles, and Information security.
I am enthusiastic about applying my knowledge and experiences to contribute to a reputable organization as a Data Engineer. I am confident that I can bring value to the team and foster personal growth while making a significant impact.
Database/ Data Warehouse - MongoDB, MySQL, Google Datastore, SQL, Oracle, BigQuery
Languages - Java, Python, Bash scripting
Big Data Ecosystems - Map-Reduce, Pig, YARN, HDFS, Apache Spark, Apache Hive, Kafka
Cloud - Kubernetes, Docker, AWS- S3, ECS, Lambda, OpenSearch, GCP
Platforms - Unix, Linux, MacOS
Build tools - Jenkins, CI-CD, Git, Maven, Gradle
Frameworks - SpringBoot, RestAPI
Schedulers- Airflow, Crontab
Data Science- NLP, Regression models, Supervised/ Unsupervised learning
