Senior Clinical Data Engineer

At MiniMed, you can begin a lifelong career of exploration and innovation, while helping make a difference in the lives of people living with diabetes around the globe. You'll lead with purpose, breaking down barriers to innovation for a more connected, compassionate world.

About The Role

MiniMed is seeking a Senior Clinical Data Engineer to join our Bioinformatics team and play a key role in developing scalable data solutions that support clinical research, medical device studies, and real-world data initiatives. This role is responsible for building and optimizing data pipelines, integrating complex data from multiple sources, and transforming raw data into high-quality datasets that enable analytics, evidence generation, and informed decision-making.

The Senior Clinical Data Engineer will collaborate with cross-functional teams, including Clinical Research, Biostatistics, R&D, and Software Engineering, to ensure data quality, consistency, and usability across a diverse data ecosystem. The ideal candidate will have strong experience with SQL, Databricks, AWS, and AWS Redshift, as well as a proven ability to operate independently and deliver results in a dynamic environment.

Responsibilities may include the following and other duties may be assigned

• Design, develop, evaluate, and maintain data pipelines, programs, and workflows used to process, validate, and analyze 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, including JSON and CSV files.
• Collect, clean, transform, and standardize raw clinical and device data into high-quality, analysis-ready datasets for statistical analysis and reporting.
• Partner with Biostatistics and study teams to understand analytical requirements and deliver finalized datasets optimized for statistical software and downstream use.
• Collaborate with Medical Device and Software Engineering teams to align on data schemas, firmware updates, data payload specifications, and system integration requirements.
• Identify data inconsistencies, perform root cause analysis, and implement solutions to ensure data quality, accuracy, and completeness.
• Support clinical data management activities, including data mining, validation, reconciliation, and issue resolution across multiple data sources.
• Contribute to the development and execution of data management plans that support study, project, and protocol timelines.
• Provide technical support for software user acceptance testing and review training materials, instructions, and documentation related to clinical data systems.
• Serve as a liaison among Clinical Research, R&D, Biostatistics, and other cross-functional stakeholders to communicate timelines, requirements, and deliverables.
• Apply software engineering best practices, including version control, CI/CD, and code review processes, to ensure reliable and maintainable solutions.
• Work independently on multiple projects in a deadline-driven environment while maintaining a high level of quality and accountability.

Required Knowledge And Experience

• Bachelor's degree in Computer Science, Data Engineering, Biomedical Engineering, Statistics or a related field.
• Minimum of 4 years of relevant experience in clinical data engineering, clinical data management, data analytics, or a related technical field.
• Strong experience with SQL development and query optimization in Databricks and AWS Redshift.
• Experience developing and maintaining data pipelines using Databricks, PySpark, AWS services, and AWS Redshift.
• Experience working with structured and semi-structured data formats, including JSON and CSV.
• Knowledge of clinical research data processes, clinical trial operations, and data quality principles.
• Strong analytical, problem-solving, and troubleshooting skills.
• Demonstrated ability to collaborate effectively across technical and non-technical teams.
• Strong written and verbal communication skills.
• Ability to work independently and manage multiple priorities in a fast-paced environment.

Preferred Qualifications

M.S/Ph.D. Computer Science, Engineering, Mathematics, Data Science

• Experience supporting clinical trials, medical device data, or regulated healthcare environments.
• Familiarity with statistical analysis datasets and collaboration with Biostatistics teams.
• Experience with Git, CI/CD pipelines, and software development lifecycle best practices.
• Knowledge of data validation, reconciliation, and regulatory expectations related to clinical data.
• Experience working with cross-functional teams including Clinical Research, R&D, and Software Engin