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AI Summary

The Senior Data Engineer will develop and maintain scalable data engineering platforms using the AWS native stack. They will design reusable modules and collaborate with agile teams to implement robust data pipelines and debugging solutions.

The Senior Data Engineer for the project will be responsible for maintaining and developing a comprehensive Data Engineering platforms. This role focuses on building scalable, reusable solutions that can be deployed across multiple countries and business environments within the project framework.

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Required Skills & Experience

 

Key Responsibilities

• Develop and maintain the Data Engineering platforms using AWS Native stack

• Design and implement generalized modules using modern Python development practices that are reusable across various countries and business settings

• Apply object-oriented programming principles to create maintainable and scalable data processing solutions

• Collaborate effectively within agile development teams to deliver high-quality solutions on schedule

• Identify root causes of issues with existing data and suggestion generation pipelines and implement robust fixes (debugging across AWS Step Functions, Glue, Athena, and Lambda)

• Leverage modern Python development tools and engineering practices to ensure code quality, testing, and deployment efficiency


Who We Are Looking For

• Advanced Python programming expertise, with particular strength in: o pandas for data manipulation and analysis o Object-oriented programming (OOP) principles and design patterns o Modern Python development tools and best practices

• AWS cloud technologies experience, specifically: o AWS Glue for ETL processes o Amazon Athena for data querying Information Sensitivity: General\Internal o DynamoDB for NoSQL data storage o AWS Step Functions and Lambda for workflow orchestration

• Strong understanding of cloud architectures, particularly AWS-based solutions

• Experience with agile software development methodologies and common project management tools (e.g., Azure DevOps)

• 5-10 years of data engineering experience with global or regional project exposure is nice to have

• Experience with modern software engineering practices including CI/CD, version control, and automated testing


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