Data Engineer (Clinical, laboratory, scientific data)

About Us Data, analytics and cybersecurity staffing. We connect professionals and companies to deliver successful projects. Job Description We are looking for an experienced Senior Data Engineer to join a data-focused project for a global pharmaceutical company. You will design, build, and maintain scalable cloud data pipelines and platforms using AWS, Python, SQL, Spark, and Databricks. Key Responsibilities Design, develop, and maintain scalable data pipelines and data-processing solutions. Build cloud-based data solutions using AWS services. Develop ETL/ELT workflows using Python, SQL, Spark, and PySpark. Work with Databricks and Dataiku for data engineering, transformation, and analytics use cases. Develop and optimize solutions involving Amazon Redshift and Amazon S3. Automate infrastructure deployments using Terraform and CloudFormation. Build and maintain CI/CD pipelines using Jenkins and Git. Containerize applications and data workloads using Docker. Monitor data workflows and troubleshoot performance or reliability issues. Produce clear technical documentation in accordance with SDLC standards. Collaborate with data engineers, architects, analysts, and global business stakeholders. Requirements 5–8 years of relevant data engineering experience. Strong hands-on experience with AWS, particularly: Amazon S3 IAM Amazon Redshift AWS Glue AWS Lambda AWS Step Functions Amazon CloudWatch Amazon SageMaker Strong programming skills in Python or Java. Advanced SQL knowledge, ideally including Amazon Redshift. 2–3 years of hands-on experience with Apache Spark or PySpark. Experience with Databricks and/or Dataiku. Experience with Terraform and AWS CloudFormation. Practical knowledge of Jenkins, Git, and Docker. Understanding of software development lifecycle processes and technical documentation. Strong communication skills and the ability to work within an international team. Previous experience in the pharmaceutical, healthcare, laboratory, or life-sciences sector. Knowledge of DSCS and DPTM platforms or related data-management environments. Experience working with regulated or validated data solutions. Familiarity with data originating from laboratory or scientific systems. Benefits Location: A hybrid working model with three days per week in the Prague office is preferred but we could consider remote candidates(EU area) as well. Contract Type: Freelance / Contract Start date: September, 2026 Time Allocation: 40 hours/week Rate: max 7000 Kč/MD