Senior Clinical Data Engineer (LATAM)

Essential functions of the job include but are not limited to:

Data Standardization & Mapping:

Spearhead the development of enterprise-level data mapping strategies that transform raw clinical data into standardized formats for high-impact analytics. Lead the adoption and governance of data standards across programs to ensure regulatory alignment and consistency.

Data Quality Assurance:

Design and implement robust, scalable validation frameworks that proactively detect and resolve systemic data issues. Serve as a strategic partner to Clinical Data Managers and cross-functional teams, driving continuous improvement in data integrity across global trials

Programming & Scripting:

Architect and maintain advanced, modular codebases using SAS to support complex data engineering workflows. Python, R, and SQL experience is highly preferred as we continue to leverage Ai tools across the industry. Establishing coding standards and mentoring junior engineers in automation, reproducibility, and performance optimization. Example use cases includes edit checks, reconciliations, exception listings, programmed protocol deviations, resource projections based on site data entry volume

Regulatory Compliance & Documentation:

Lead compliance initiatives to ensure all data systems and workflows meet GCP, FDA 21 CFR Part 11, and evolving global regulatory requirements. Define documentation protocols and oversee audit trail governance to support inspection readiness and transparency.

Reporting & Visualization:

Develop and operationalize dynamic dashboards and analytics tools that provide real-time insights into data quality, trial progress, and operational KPIs. Translate complex datasets into actionable intelligence for clinical and regulatory stakeholders.

Collaboration & Cross-Functional Support:

Act as a strategic liaison between Clinical Data Engineering and Biostatistics, Clinical Operations, and Regulatory Affairs. Translate clinical and scientific requirements into scalable technical solutions that support study execution and data delivery.

Database Design & Optimization:

Lead the design and optimization of secure, high-performance relational databases and data lakes. Ensure infrastructure scalability, query efficiency, and data governance for large-scale clinical datasets.