Senior Data Engineer
About The Position
As a Senior Data Engineer at Clario, you will play a critical role in designing and building the modern data infrastructure that powers advanced analytics, machine learning, and AI‑driven innovation across our clinical technology platform. You will architect cloud‑native, scalable, and secure data systems that support regulated clinical environments, ensuring data flows are reliable, compliant, and optimized for next-generation clinical insights. Partnering closely with data scientists, AI engineers, software engineers, and product teams, you will help evolve a data ecosystem capable of supporting large-scale clinical datasets, imaging studies, and AI‑enabled applications.
Requirements
- 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
Nice To Haves
- Experience with AI/ML data pipelines or generative AI workflows
- Experience handling large-scale or high-volume datasets
- Experience working with medical imaging data or complex healthcare data structures
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
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
