Data engineer

Skill Set: AWS Cloud Technologies: Strong command of Apache Spark (3-5 years) AWS Glue expertise (3-5 years) Databricks and pyspark. PySpark Application Development: Extensive experience in designing, developing, troubleshooting, and debugging PySpark applications Proven track record in processing and handling large datasets Performance Tuning: Hands-on experience in performance tuning Spark applications Skills to optimize Spark code for scalability, performance, and maintainability Microservices Development: Proficient in developing microservices using AWS Lambda, SNS, DynamoDB (1-5 years) Code Management: Strong proficiency in using GitHub for efficient code management and sharing Nice to have: Experience in Databricks Experience in the node.js, vue.js. Job Description: We are seeking an experienced data engineer to contribute to a high data volume Electronic Medical Records (EMR) application. This critical system not only requires ongoing production maintenance but also demands enhancements through integration with Machine Learning (ML) and Master Data applications. In the future, there's a plan to migrate the existing EMR application to AWS Glue. The ideal candidate will possess robust data engineering expertise, adept at designing, developing, and fine-tuning applications. Exposure to various design patterns within the data engineering paradigm is crucial for success in this role. Our development process adheres to an agile methodology, with Program Increment (PI) planning occurring every six weeks, equivalent to three sprints. If you are a skilled data engineer who thrives in an agile environment and has a solid background in designing and optimizing applications, we invite you to join our dynamic team.