Proven track record of innovation and expertise in Data Engineering
Tenure in engineering and delivering complex projects
Ability to work in multi-cloud environments
Deep understanding and application of modern data processing technology stacks. For example, AWS Redshift, Azure Parallel Data Warehouse, Spark, Hadoop ecosystem technologies, and others
Knowledge of how to architect solutions for data science and analytics such as building production-ready machine learning models and collaborating with data scientists
Knowledge of agile development methods including core values, guiding principles, and essential agile practices
Atleast 5 years of experience in Big Data Domain.
Candidate must have hands-on experienece with python, SQL and AWS.
Must have health care experience.
At least three years of experience of using Big Data systems.
Strong SQL writing and optimizing skills for AWS Redshift and Azure SQL Data Warehouse.
Strong experience working in Linux-based environments.
Experience with messaging, queuing, and workflow systems, especially Kafka or Amazon Kinesis
Experience with non-relational, NoSQL databases and various data-storage systems
Experience working with Machine Learning and Data Science teams, especially creating architecture for experimentation versus production execution.
Experience integrating with CI tools programmatically