Clinical Data Engineer

Job Title: Clinical Data Engineer 

Contract Type: 12-Month Fixed-Term Contract 

Location: Ireland (Hybrid/Onsite depending on business needs) 

Working Hours: 40 hours per week 

Start Date: Immediate requirement 

Role Overview: This organization is executing a multi-year Clinical Supply Chain Data & Analytics Strategy Roadmap designed to transform how clinical trial and supply chain data is collected, governed, and analyzed. The program focuses on building scalable data platforms, improving data quality and compliance, and enabling advanced analytics to support operational and strategic decision-making across clinical operations. The Clinical Data Engineer will be a key contributor to this initiative, supporting the design and implementation of robust data pipelines and analytics-ready datasets. This role is well suited to an early-career data engineer with a strong technical foundation, exposure to regulated data environments, and a strong interest in clinical trials, life sciences, or healthcare data. You will work closely with data architects, analysts, and cross-functional stakeholders to convert raw clinical and operational data into trusted, high-quality datasets that enable reporting, dashboards, and advanced analytical use cases. 

Key Responsibilities: 

Data Engineering & Pipeline Development 

• Design, build, and maintain automated data pipelines to ingest, transform, and load clinical trial and supply chain data from multiple systems.
• Implement ETL/ELT processes using modern data transformation tools such as dbt or equivalent frameworks.
• Ensure data pipelines are scalable, reliable, maintainable, and meet performance and availability requirements.
• Support onboarding of new data sources and enhancements to existing data integrations. 

Data Modelling & Architecture 

• Design and implement data models (e.g., dimensional, analytical schemas) optimized for reporting and analytics.
• Transform raw and semi-structured data into standardized, analytics-ready tables and views.
• Align data structures with enterprise data architecture and long-term analytics strategy. 

Data Quality, Governance & Compliance 

• Develop and execute data validation, reconciliation, and cleansing processes to ensure high data quality.
• Apply data governance standards to maintain data integrity, traceability, and regulatory compliance (e.g., GxP, GDPR).
• Contribute to documentation, metadata management, and audit-ready data assets. Analytics & Business Support
• Analyze clinical and operational datasets to identify trends, anomalies, and insights.
• Support the creation of dashboards, reports, and visualizations for operational and leadership stakeholders.
• Collaborate with analytics and data science teams by delivering reliable datasets for downstream use. 

Delivery & Independent Ownership 

• Manage assigned tasks and workstreams with minimal supervision, ensuring timely and high-quality delivery.
• Proactively identify process improvements, automation opportunities, and data platform enhancements. 

Must Have Requirements: 

Candidates must demonstrate the following: 

• Bachelor’s degree in Data Science, Computer Science, Statistics, or a related field.
• 0-3 years of hands-on experience in data engineering, data analytics, data curation, or a closely related role.
• Strong proficiency in SQL, including writing complex queries and transformations.
• Practical experience with ETL/ELT pipelines, data ingestion, and data transformation processes.
• Working knowledge of Python and/or R for data manipulation and analysis.
• Experience working with structured and semi-structured datasets.
• Understanding of data modeling concepts (e.g., fact/dimension tables, analytical schemas).
• Familiarity with data quality management and validation techniques.
• Awareness of data governance and compliance principles in regulated environments (e.g., GDPR, GxP concepts).
• Experience using data visualization or BI tools such as Tableau or Power BI.
• Strong analytical thinking, attention to detail, and problem-solving skills.
• Ability to work independently, manage multiple priorities, and meet deadlines.
• Strong written and verbal communication skills, with the ability to collaborate across technical and non-technical teams. 

Nice to Have Requirements: 

The following are desirable but not essential: 

• Previous experience within clinical trials, life sciences, healthcare, or pharmaceutical environments.
• Hands-on experience with dbt in a production or project-based setting.
• Certification in Data Analytics, Data Engineering, or a related discipline.
• Certification or experience with specific ETL tools or platforms.
• Familiarity with clinical trial systems (e.g., CTMS, IRT, EDC) and associated data structures.
• Experience working in Agile or Scrum delivery environments; JIRA certification is an advantage.
• Exposure to cloud-based data platforms and modern analytics stacks.
• Basic experience or academic exposure to machine learning or predictive modeling.
• Experience contributing to large-scale, multi-year data transformation programs.