Senior Clinical Data Engineer: Scalable Pipelines

MiniMed; Lisboa; Presencial; EUR 65 000 - 90 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Flexible benefits package

Competitive compensation

Resumo da oferta

MiniMed seeks a Senior Clinical Data Engineer to join its Bioinformatics team, developing scalable data pipelines for clinical research, medical device studies, and real-world data initiatives.

The role focuses on transforming raw data into high-quality datasets for analytics and decision-making, with collaboration across Clinical Research, Biostatistics, R&D, and Software Engineering to ensure data quality and usability.

Qualificações

• Bachelor’s degree in Computer Science, Data Engineering, Biomedical Engineering, Statistics or related field.
• Four or more years of relevant experience in clinical data engineering, data analytics, or 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 with JSON and CSV data formats.

Responsabilidades

• Design, develop, and maintain data pipelines and workflows for processing clinical and medical device data.
• Build automated ETL/ELT solutions using Databricks, PySpark, SQL, and AWS to ingest and transform data.
• Prepare analysis-ready datasets for statistical analysis and reporting.
• Collaborate with Biostatistics and study teams to meet analytical requirements.
• Coordinate with Medical Device and Software Engineering teams on data schemas and system integration.

Conhecimentos

SQL

Databricks

AWS

PySpark

Data pipelines

Data quality

CI/CD

Git

Communication

Independent work

Formação académica

Bachelor’s degree

Ferramentas

AWS Redshift

Descrição da oferta de emprego

MiniMed seeks a Senior Clinical Data Engineer to join its Bioinformatics team, developing scalable data pipelines for clinical research, medical device studies, and real-world data initiatives.

The role focuses on transforming raw data into high-quality datasets for analytics and decision-making, with collaboration across Clinical Research, Biostatistics, R&D, and Software Engineering to ensure data quality and usability.