About the role

Senior Data Engineer building cloud-native data infrastructure that powers analytics and AI at Clario. Collaborating with cross-functional teams to enhance data capabilities for clinical trials.

Responsibilities

Design, build, and maintain scalable ETL/ELT pipelines for structured and unstructured clinical data
Develop and optimize data models supporting analytics, reporting, and machine learning workflows
Build and maintain cloud-native data architectures within AWS environments
Develop pipelines that support AI and machine learning model development and deployment
Operationalize and productionize machine learning models developed by Data Science teams
Ensure data quality, integrity, governance, and regulatory compliance
Improve performance, reliability, and scalability of large-scale data platforms
Collaborate closely with data scientists, AI engineers, software engineers, and product teams
Translate clinical and business requirements into scalable data engineering solutions
Implement monitoring, observability, and automated validation across data pipelines
Contribute to data engineering standards, architecture design, and platform evolution

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related quantitative field
5+ years of experience in data engineering or data platform development
Strong proficiency in Python and SQL
Experience designing and maintaining scalable data pipelines in cloud environments
Hands-on experience with AWS services such as S3, Redshift, Glue, Lambda, EMR, or similar
Strong understanding of data modeling, schema design, and performance optimization
Experience supporting machine learning or AI workflows in production environments
Experience working with distributed or large-scale data architectures
Strong analytical, problem-solving, and communication skills
Experience in regulated industries (healthcare, life sciences, clinical research) is a plus