Analysis Skills, Clinical Data, Clinical Research, Data Analysis, Data Management, Data Modeling, Data Processing, Data Quality, Data Sets, Documentation, HIPAA (Health Insurance Portability and Accountability Act), Healthcare, Identify Issues, Maintain Compliance, Medical Research, Problem Solving Skills, Quality Monitoring, Regulatory Compliance, Research Skills, SQL (Structured Query Language), Technical Research, Traceability, Training Data Sets, Validation Testing
We are a US-based company focused on advancing clinical research and medical technologies. We are seeking a Research Data Engineer to support clinical research activities by building and maintaining reliable data pipelines and preparing high-quality datasets for researchers and analysts. This role emphasizes batch data processing, data quality, data transformation and processing and enabling efficient, compliant access to research data.
Essential Duties and Responsibilities
Clinical Research Data Support:
- Ingest, process, and manage clinical and research datasets from internal and external sources.
- Design data models and datasets optimized for researcher and analyst use.
- Maintain datasets used in research studies, ensuring consistency, traceability, and documentation.
Batch Data Engineering:
- Design, build, and maintain batch data pipelines for scheduled ingestion, transformation, and delivery.
- Optimize and monitor batch workflows to ensure performance, reliability, and scalability.
- Troubleshoot and resolve issues in data pipelines and scheduled jobs.
Data Quality and Governance:
- Implement data validation, quality checks, and monitoring processes.
- Identify and resolve data inconsistencies, anomalies, and gaps.
- Ensure compliance with healthcare data regulations (e.g., HIPAA, GDPR).
Analytics Enablement:
- Partner with researchers and analysts to deliver clean, well-structured datasets.
- Develop SQL queries and data transformations to support reporting and analysis.
- Assist with exploratory data analysis and data preparation workflows.
Collaboration and Documentation:
- Work cross-functionally with clinical, analytics, and engineering teams.
- Document data pipelines, schemas, and workflows to ensure transparency and reproducibility.