Senior Data Engineer

• Strong commercial experience in Data Engineering (around 5–10 years).
• Advanced Python programming skills, including pandas, OOP, and writing clean, reusable code.
• Hands-on experience with AWS Glue, Amazon Athena, DynamoDB, AWS Step Functions, and AWS Lambda.
• Solid experience designing, developing, and maintaining data pipelines.
• Good understanding of cloud-based data architectures and data processing solutions.
• Experience working in agile development environments.
• Ability to independently troubleshoot and debug complex data and pipeline issues.
• Experience working in international or distributed project environments.

Nice to have:

• Experience with Veeva or similar platforms.
• Exposure to pharmaceutical or healthcare data environments.
• Experience with CI/CD, automated testing, and modern software engineering practices.
• Familiarity with Azure DevOps or similar development and delivery platforms.

• Design, develop, and maintain scalable data pipelines and data processing solutions.
• Build reusable and configurable modules in Python to support different business requirements and environments.
• Apply object-oriented programming (OOP) principles and modern Python engineering practices for maintainable, scalable solutions.
• Work hands-on with AWS services including Glue, Athena, DynamoDB, Step Functions, and Lambda.
• Investigate and resolve issues in existing data pipelines with root-cause analysis and robust fixes.
• Support platform changes and migrations, including pipeline updates, validation, and end-to-end testing.
• Contribute to code quality via testing, version control, and CI/CD practices.
• Collaborate with developers, data specialists, and stakeholders in an agile delivery environment.