Senior AWS Data Engineer
Posted Updated 5
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O projekcie:
Offer:
- Private medical care- Co-financing for the sports card- Constant support of dedicated consultant- Employee referral program
Wymagania:
- 5-10 years of data engineering experience with global or regional project exposure
- Advanced Python programming expertise, with particular strength in pandas for data manipulation and analysis; Object-oriented programming (OOP) principles and design patterns; Modern Python development tools and best practices
- AWS cloud technologies experience, specifically: AWS Glue for ETL processes, Amazon Athena for data querying Information Sensitivity: General\Internal, DynamoDB for NoSQL data storage, 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)
Nice to have:
- Basic knowledge of Veeva platforms
- Experience with modern software engineering practices including CI/CD, version control, and automated testing
- Background in pharmaceutical or healthcare data environments
Codzienne zadania:
- 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
- Support the migration of the suggestion generation platform to a new CRM system, including setup activities such as use case pipeline updates, validation through end-to-end run checks and suggestion validation, and execution of migration tasks
- 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