Senior Clinical Data Engineer
Listed on 2026-10-26
-
IT/Tech
Data Engineering, Data Analyst
Flexible
Virtual, Madrid, Spain
Watford, Hertfordshire, United Kingdom
Virtual, Lisbon, Portugal
Virtual, Milano, Italy
Full time
R-802143
At Mini Med, 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
Mini Med 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…
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