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Data Architect
hace 6 días
Responsibilities
Design, develop, and maintain ETL pipelines using PySpark, ensuring data quality and performance Utilize AWS services (EMR, Glue) for data processing and storage optimization Implement dimensional modeling and manage data lakehouse solutions Develop and maintain CI/CD pipelines with AWS CDK and GitHub Actions Actively participate in SCRUM processes and use JIRA for task management Work with stakeholders to understand data requirements and deliver solutions Mentor junior engineers and stay updated on industry trends
Requirements
Experience with PySpark At least 7 years of total experience in building ETL pipelines, with preference given to experience in Spark (Scala/Python) At least 5 years of experience with Amazon AWS Data & Analytics Toolset (EMR/Glue) OR Databricks, with preference for AWS Glue Strong understanding of Data Lakehouse/Data warehouse principles, such as Dimensional Modelling A working knowledge of Continuous Integration/Continuous Deployment practices is required, with practical experience in DevOps principles, for example, AWS CDK and GitHub Actions Experience with the agile SCRUM delivery model, along with proficiency in JIRA Strong interpersonal skills are essential Useful links-
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