Trainee Data Engineer - MedInsight (Dev)

What Is Expected Of You At This Level

Expectations At The Internship Level

• Organizational Acumen: Develop a comprehensive understanding of the organization’s mission, values, and strategic objectives. Consistently align your contributions with the broader goals of the team and company.
• Commitment to Learning: Exhibit a proactive and enthusiastic approach to learning throughout the internship. Actively participate in training sessions, seek out opportunities for professional development, and demonstrate continual growth in bo.h technical and business knowledge.
• Technical Proficiency: Acquire familiarity with the key technologies and tools utilized by the data engineering team, including but not limited to Databricks, SQL, PySpark, and Azure DevOps. Strive to deepen your practical skills in these areas through hands-on project work.
• Increasing Autonomy: Begin your internship by working under general supervision, with the expectation of progressively taking on greater responsibility and executing tasks with increased independence as your experience and confidence grow.
• Collaborative Engagement: Operate effectively within a distributed and diverse global team environment. Demonstrate strong communication skills and a collaborative mindset while working with colleagues across various time zones and locations.
• AI Integration Exposure: Gain practical exposure to the integration of artificial intelligence (AI) technologies within data engineering projects, enhancing your understanding of how advanced analytics and machine learning can drive business value.
  

What You Must Have

• Foundational knowledge of SQL, Python (including PySpark), and familiarity Object-Oriented Programming (OOP) concepts.
• Strong analytical and problem-solving skills with the ability to troubleshoot and optimize data engineering processes.
• A basic understanding of data engineering concepts, with a willingness to learn and apply new technologies.
• Excellent communication and teamwork abilities.
• Hands-on experience with artificial intelligence (AI) or machine learning (ML) projects is highly desirable. Exposure to integrating AI/ML models within data pipelines or familiarity with AI frameworks will be considered a significant advantage and may provide the candidate with a competitive edge in this role.
  

Educational Requirements