Artificial Intelligence β’ Machine Learning β’ Natural Language Processing β’ Neuro-Linguistic Programming β’ Data Science
201 - 500
November 23
Artificial Intelligence β’ Machine Learning β’ Natural Language Processing β’ Neuro-Linguistic Programming β’ Data Science
201 - 500
β’ Design, develop, and maintain robust and scalable ETL pipelines to acquire, transform, and load data from various sources into our data ecosystem. β’ Collaborate with cross-functional teams to understand data requirements and develop efficient data acquisition and integration strategies. β’ Implement data transformation logic using Python and other relevant programming languages and frameworks. β’ Utilize AWS Glue or similar tools to create and manage ETL jobs, workflows, and data catalogs. β’ Optimize and tune ETL processes for improved performance and scalability, particularly with large data sets. β’ Apply methodologies and techniques for data matching, deduplication, and aggregation to ensure data accuracy and quality. β’ Implement and maintain data governance practices to ensure compliance, data security, and privacy. β’ Collaborate with the data engineering team to explore and adopt new technologies and tools that enhance the efficiency and effectiveness of data processing.
β’ Bachelor's degree in Computer Science, Information Systems, related fields or equivalent years of work experience. β’ 7+ years of experience as a Data Engineer, with a focus on ETL processes and data integration. β’ Professional experience with Spark and AWS pipeline development required.
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10,000+
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