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Key Responsibilities:
- Develop, maintain, and optimize ETL processes using AWS Glue, PySpark, and SQL to support data-driven initiatives and data warehousing needs.
- Work with various database engines (Oracle, PostgreSQL, Amazon S3, PostgreSQL, and Athena) and interact with external APIs to extract and load data.
- Leverage AWS services including AWS Glue, CloudFormation, and Lambda to manage, monitor, and scale data workflows effectively.
- Write modular, testable, and well-documented code following Python, AWS Glue, and Lambda best practices.
- Manage CI/CD pipelines and ensure strong testing, validation, and code quality assurance.
- Collaborate with cross-functional teams to define data requirements, troubleshoot issues, and support business objectives.
- Implement data governance, metadata management, and data quality practices.
- Participate in Agile-Scrum teams, contributing to sprints and iterative development processes.
- Excellent teamwork and communication skills, with the ability to work effectively in a collaborative environment.
Qualifications:
- Bachelor’s degree in Computer Science or Data Analytics, or a related field.
- Minimum of 3 years of hands-on experience with AWS services, including extensive experience with AWS Glue, CloudFormation, and Lambda.
- Minimum of 3 years of experience in Python/PySpark and SQL for data processing, transformation, and querying.
- Proven experience in pulling and integrating data using APIs, with a preference for GraphQL API knowledge.
- Strong knowledge of Git, GitLab, and Bitbucket for code versioning and maintainability.
- Excellent analytical and problem-solving skills with a keen attention to detail.
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