Job Summary
AWS + Data Engineering
Overview of the Role
The AWS Data Engineer will play a pivotal role in developing high-impact data solutions for clients in the pharmaceutical sector. This position focuses on leveraging AWS cloud technologies and advanced data engineering practices to drive analytics, optimize data workflows, and support business-critical pharmaceutical initiatives. The role contributes directly to improving the efficiency, compliance, and innovation of data-driven processes within the Life Sciences and Healthcare industry.
Detailed Responsibilities
- Design, build, and maintain scalable data pipelines and architectures using AWS services (e.g., S3, Redshift, Glue, EMR, Lambda).
- Collaborate with cross-functional teams—including business analysts, data scientists, and application developers—to deliver integrated data solutions tailored to pharmaceutical business needs.
- Ensure data quality, integrity, and security in compliance with industry standards and regulatory requirements (such as FDA, HIPAA, GxP).
- Implement ETL processes to ingest, transform, and manage large data sets from multiple sources.
- Optimize data storage and retrieval for analytics and reporting purposes.
- Monitor and troubleshoot data workflows, resolving issues to ensure reliable operations.
- Document data engineering processes and contribute to knowledge sharing within the team.
- Stay current with emerging technologies and best practices in AWS and pharmaceutical data engineering.
Skill Requirements
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline.
- 3+ years of hands-on experience in data engineering, preferably within the pharmaceutical or healthcare domain.
- Proficiency with AWS services for data engineering and analytics (e.g., S3, Redshift, Glue, EMR, Lambda).
- Strong programming skills in Python, SQL, and/or Scala.
- Experience in designing, developing, and optimizing ETL pipelines.
- Knowledge of data governance, security, and regulatory compliance specific to Life Sciences and Healthcare.
- Familiarity with data modeling, warehousing, and reporting tools.
- Excellent problem-solving, analytical, and communication skills
Key Responsibilities
AWS + Data Engineering
Overview of the Role
The AWS Data Engineer will play a pivotal role in developing high-impact data solutions for clients in the pharmaceutical sector. This position focuses on leveraging AWS cloud technologies and advanced data engineering practices to drive analytics, optimize data workflows, and support business-critical pharmaceutical initiatives. The role contributes directly to improving the efficiency, compliance, and innovation of data-driven processes within the Life Sciences and Healthcare industry.
Detailed Responsibilities
- Design, build, and maintain scalable data pipelines and architectures using AWS services (e.g., S3, Redshift, Glue, EMR, Lambda).
- Collaborate with cross-functional teams—including business analysts, data scientists, and application developers—to deliver integrated data solutions tailored to pharmaceutical business needs.
- Ensure data quality, integrity, and security in compliance with industry standards and regulatory requirements (such as FDA, HIPAA, GxP).
- Implement ETL processes to ingest, transform, and manage large data sets from multiple sources.
- Optimize data storage and retrieval for analytics and reporting purposes.
- Monitor and troubleshoot data workflows, resolving issues to ensure reliable operations.
- Document data engineering processes and contribute to knowledge sharing within the team.
- Stay current with emerging technologies and best practices in AWS and pharmaceutical data engineering.
Skill Requirements
- Bachelor’s or Master’s degree in Computer Science, Information Technology, Engineering, or a related discipline.
- 3+ years of hands-on experience in data engineering, preferably within the pharmaceutical or healthcare domain.
- Proficiency with AWS services for data engineering and analytics (e.g., S3, Redshift, Glue, EMR, Lambda).
- Strong programming skills in Python, SQL, and/or Scala.
- Experience in designing, developing, and optimizing ETL pipelines.
- Knowledge of data governance, security, and regulatory compliance specific to Life Sciences and Healthcare.
- Familiarity with data modeling, warehousing, and reporting tools.
- Excellent problem-solving, analytical, and communication skills