Data Engineer

About the RoleWe are seeking multiple Data Engineers to join a global data and analytics programme within a highly regulated pharmaceutical and life sciences environment. You will play a key role in designing, building, and maintaining scalable data pipelines that support critical business initiatives across clinical development, manufacturing, process development, and active pharmaceutical ingredient data domains.Working within a modern cloud data ecosystem, you will help deliver trusted, high-quality data products while ensuring compliance with GxP regulations and industry standards.Key ResponsibilitiesDesign, develop, and orchestrate automated data ingestion and transformation pipelines across multiple enterprise systems, including SAP, LIMS, and MES.Build scalable ELT/ETL solutions using SQL and Python within a modern cloud data platform.Develop modular and reusable transformation logic following medallion/layered architecture principles.Implement workflow orchestration and scheduling for batch and streaming data pipelines.Drive CI/CD adoption, automated testing, version control, and deployment best practices.Embed data quality, lineage, monitoring, and observability controls to ensure data integrity and reliability.Optimize data processing performance, scalability, and platform costs.Ensure all solutions comply with ALCOA+ principles, 21 CFR Part 11, EMA, and other regulated industry requirements.Support the delivery of enterprise data products and analytics capabilities that enable informed business decisions across global operations.Required Technical SkillsApache Airflow (workflow orchestration)Snowflake (cloud data platform)dbt (data transformation and modelling)Talend (data integration)Amazon S3 (data lake storage)GitLab (source control and CI/CD)Collibra (data governance and lineage)Essential Experience3-10 years of Data Engineering experience.Strong SQL and Python development skills.Experience designing and implementing ELT/ETL pipelines.Knowledge of dimensional modelling and medallion architecture.Hands-on experience with CI/CD pipelines and Git-based development workflows.Understanding of data quality frameworks, lineage, observability, and monitoring.Experience with performance tuning and cloud cost optimisation.Ability to work within complex enterprise environments and collaborate with cross-functional teams.Desired Domain ExperienceExperience within one or more of the following areas would be highly advantageous:Clinical trial dataPharmaceutical manufacturingProcess developmentActive ingredient data managementKnowledge graph solutionsSubstance and product data domainsGxP-regulated environments