Data Engineer – Regulatory Affairs & Quality Medicine

At Next. Link, we are looking for an experienced Senior Data Engineer to join our consulting team and collaborate with one of our leading clients in the pharmaceutical industry. You will support the Regulatory Affairs and Quality Medicine data domains, contributing to the development, integration, and optimization of scalable data solutions in AWS, Snowflake, and Snap.

Logic environments. This hands-on role focuses on designing, developing, and maintaining reliable cloud-based data pipelines, ensuring data quality, performance, and effective integration across enterprise systems. Main Responsibilities Design, develop, and maintain scalable ETL/ELT pipelines and data integrations using Python/Py.

Spark, SQL, AWS, and Snowflake. Work with AWS services (S3, Lambda, Glue) and Snowflake for data ingestion, transformation, modeling, and performance optimization. Support data integration workflows, including Snap. Logic where applicable. Implement coding best practices, version control (Git), CI/CD processes, and automated testing.

Ensure data quality, governance, lineage, and metadata management across data solutions. Monitor, troubleshoot, and optimize data pipelines in cloud-based, distributed, and containerized environments. Collaborate with cross-functional teams, taking ownership of delivery from requirements gathering through deployment and ongoing support.

Requirements

Mandatory Bachelor's or Master's degree in Computer Science, Engineering, Data/Information Systems, or a related field. Over 5 years of professional experience in Data Engineering, Analytics Engineering, or similar data-focused roles, including hands-on development and maintenance of cloud-based data pipelines in production environments.

Strong programming skills in Python/Py. Spark and SQL, including data transformation and optimization. Practical experience with AWS (S3, Lambda, Glue) in production environments. Hands-on experience with Snowflake, including data warehousing, modeling, ingestion, and performance optimization. Solid understanding of ETL/ELT architectures, data modeling, Git, CI/CD, automated testing, and production monitoring.

Familiarity with data governance, data quality, metadata management, and data lineage. Strong communication skills, fluent English, and a proactive, autonomous, problem-solving mindset. Desirable Experience with Snap. Logic or other i. PaaS integration platforms. Familiarity with Collibra or similar data governance and metadata management tools.

Experience working in Agile environments and with containerized or distributed data solutions. Spanish language skills. Previous experience in pharmaceutical, Regulatory Affairs, or Quality Medicine data domains. Service Setup Duration: 6–12 months. Working model: Fully remote.