Senior Data Engineer (PySpark)

Senior Data Engineer (PySpark) Job Title: Senior Data Engineer Location: Remote Experience: 5-10 Years 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.