Source description
About the role
●Design, develop, and implement scalable and efficient data pipelines in the cloud using Python, SQL, and relevant technologies.
● Build and maintain data infrastructure on platforms such as AWS, leveraging services like EMR, Redshift, and others.
● Collaborate with data scientists, analysts, and other stakeholders to understand their requirements and provide the necessary data solutions.
● Develop and optimize ETL (Extract, Transform, Load) processes to ensure the accuracy, completeness, and timeliness of data.
● Create and maintain data models, schemas, and database structures using PostgreSQL and other relevant database technologies.
● Experience reporting tools such as Superset, (good to have : Domo, or Tableau, Quicksight) to develop visually appealing and insightful data visualizations and dashboards.
● Monitor and optimize the performance and scalability of data systems, ensuring high availability and reliability.
● Implement and maintain data security and privacy measures to protect sensitive information.
● Collaborate with the engineering team to integrate data solutions into existing applications or build new applications as required.
● Stay up-to-date with industry trends, emerging technologies, and best practices in data engineering
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