Senior Clinical Data Engineer

About the role

MiniMed is seeking a Senior Clinical Data Engineer to join its Bioinformatics team and build scalable data solutions that support clinical research, medical device studies and real-world data initiatives. The role covers designing and optimizing data pipelines, integrating data from many sources and turning raw data into high-quality datasets for analytics and evidence generation. It works closely with Clinical Research, Biostatistics, R&D and Software Engineering teams.

Key responsibilities

• Design, develop, evaluate and maintain data pipelines, programs and workflows for processing, validating and analyzing clinical and medical device data.
• Build and support automated ETL/ELT solutions using Databricks, PySpark, SQL and AWS services to ingest and transform structured and semi-structured data such as JSON and CSV.
• Clean, transform and standardize raw clinical and device data into analysis-ready datasets for statistical analysis and reporting.
• Partner with Biostatistics and study teams to deliver datasets optimized for statistical software.
• Work with Medical Device and Software Engineering teams on data schemas, firmware updates, data payloads and system integration.
• Identify data inconsistencies, run root cause analysis and fix issues to ensure data quality, accuracy and completeness.
• Support clinical data management activities such as data mining, validation, reconciliation and issue resolution.
• Contribute to data management plans and provide technical support for software user acceptance testing and training materials.
• Act as a liaison between Clinical Research, R&D, Biostatistics and other stakeholders, and apply version control, CI/CD and code review practices.

Required profile

• Bachelor's degree in Computer Science, Data Engineering, Biomedical Engineering, Statistics or a related field.
• Minimum 4 years of experience in clinical data engineering, clinical data management, data analytics or a related technical field.
• Knowledge of clinical research data processes, clinical trial operations and data quality principles.
• Strong analytical, problem-solving and troubleshooting skills, and ability to work independently and across technical and non-technical teams.
• Preferred: M.S./Ph.D., experience with clinical trials or regulated healthcare, familiarity with statistical analysis datasets, and knowledge of data validation, reconciliation and regulatory expectations.

Required skills

• SQL development and query optimization in Databricks and AWS Redshift.
• Data pipelines with Databricks, PySpark, AWS services and AWS Redshift.
• Structured and semi-structured data formats such as JSON and CSV.
• Preferred: Git, CI/CD pipelines and software development lifecycle best practices.

What we offer

• A competitive salary and a flexible benefits package.