Data Engineer

About the Opportunity

We are looking for a highly skilled Senior Data Engineer (PySpark) to join a global data transformation initiative within the pharmaceutical domain. The role involves designing, developing, and optimizing large-scale data pipelines and ETL/ELT processes on modern Data Lake platforms.

This is a fully remote opportunity with exposure to international teams, large-scale data ecosystems, and modern cloud-based data engineering practices.

Key Responsibilities

• Design, develop, and optimize ETL/ELT pipelines using PySpark and Python.
• Build scalable data flows from source systems to Data Lake environments.
• Develop and support data integration and transformation processes.
• Ensure data quality, performance, and reliability of data pipelines.
• Document technical solutions and maintain development standards.
• Collaborate with cross-functional teams in Agile Scrum environments.
• Participate in sprint planning, estimation, and delivery activities.
• Work with Azure DevOps, Jira, and Confluence for project execution.

Required Skills

• Strong experience in PySpark and Python.
• Solid background in Data Engineering.
• Hands-on experience with ETL/ELT design and development.
• Experience working with Data Lakes and large-scale data processing.
• Strong SQL and data modeling skills.
• Experience in Agile/Scrum methodologies.
• Familiarity with Azure DevOps and/or Jira.
• Experience using Confluence for documentation.
• Excellent verbal and written communication skills.

Preferred Skills

• Experience with Palantir Foundry.
• Exposure to Databricks, Snowflake, Azure Data Factory, or similar platforms.
• Experience working with global or distributed teams.

Education

Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.