Senior Clinical Data Engineer

Flexible

Si ricordi di controllare il suo CV prima di candidarsi. Inoltre, si assicuri di leggere tutti i requisiti relativi a questo ruolo.

Virtual, Madrid, Spain

Watford, Hertfordshire, United Kingdom

Virtual, Lisbon, Portugal

Virtual, Milano, Italy

Full time

R-802143

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:

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• 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:

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• 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.