Senior Clinical Data Engineer — Remote Data Pipelines

MiniMed; España; Presencial; EUR 70.000 - 110.000; Jornada completa

Descripción de la vacante

MiniMed is recruiting a Senior Clinical Data Engineer to join our Bioinformatics team. You will build scalable data pipelines, integrate diverse data sources, and transform raw data into analysis-ready datasets for clinical research and real-world studies.

Work with Clinical Research, Biostatistics, R&D, and Software Engineering to ensure data quality and usability across a complex ecosystem. Strong SQL, Databricks, AWS, and Redshift experience are essential.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

SQL

Databricks

AWS

PySpark

ETL/ELT

Data pipelines

Data modeling

CI/CD

Educación

Bachelor's degree in Computer Science

MS/PhD (preferred)

Herramientas

Git

CI/CD pipelines

AWS Redshift

Descripción del empleo

MiniMed is recruiting a Senior Clinical Data Engineer to join our Bioinformatics team. You will build scalable data pipelines, integrate diverse data sources, and transform raw data into analysis-ready datasets for clinical research and real-world studies.

Work with Clinical Research, Biostatistics, R&D, and Software Engineering to ensure data quality and usability across a complex ecosystem. Strong SQL, Databricks, AWS, and Redshift experience are essential.