Data Engineer – Clinical, Laboratory, Scientific Data, AWS

This is a fully remote position, open to applicants in Europe.

📋 Description

• Design, develop, and sustain scalable data pipelines and data-processing solutions.

• Create cloud-based data solutions utilizing AWS services.

• Develop and enhance ETL/ELT workflows using Python, SQL, Spark, and PySpark.

• Collaborate with Databricks and Dataiku for data engineering, transformation, and analytics scenarios.

• Create and refine solutions involving Amazon Redshift and Amazon S3.

• Automate infrastructure deployments utilizing Terraform and CloudFormation.

• Establish and maintain CI/CD pipelines using Jenkins and Git.

• Containerize applications and data workloads with Docker.

• Monitor data workflows and resolve performance or reliability challenges.

• Generate technical documentation adhering to SDLC standards.

• Work alongside data engineers, architects, analysts, and global business stakeholders.

• Contribute to a data-centric project for a global pharmaceutical organization.

⛳️ Requirements

• 5–8 years of pertinent data engineering experience.

• Robust hands-on experience with AWS, particularly Amazon S3, IAM, Amazon Redshift, AWS Glue, AWS Lambda, AWS Step Functions, Amazon CloudWatch, and Amazon SageMaker.

• Strong programming capabilities in Python or Java.

• Advanced SQL expertise, ideally including Amazon Redshift.

• 2–3 years of practical experience with Apache Spark or PySpark.

• Experience with Databricks and/or Dataiku.

• Familiarity with Terraform and AWS CloudFormation.

• Practical knowledge of Jenkins, Git, and Docker.

• Understanding of software development lifecycle processes and technical documentation.

• Excellent communication skills and ability to collaborate within an international team.

• Previous experience in the pharmaceutical, healthcare, laboratory, or life sciences domain.

• Knowledge of DSCS and DPTM platforms or similar data-management environments.

• Experience working with regulated or validated data solutions.

• Familiarity with data originating from laboratory or scientific systems.

🏝️ Benefits

• Freelance / contract engagement.

• 40 hours/week time allocation.

• Remote position.

• Start date: September, 2026.