Data Engineer

We are seeking a highly motivated and skilled Data Engineer/Data Scientist to be a member of our internal study teams and the operational backend of our digital biomarker platform. This individual will support the development, optimization, and maintenance of robust operational data analysis pipelines that ensure the quality and integrity of digital biomarker data collected during customer clinical trials.

• Bachelor’s or Master’s degree in Data Science, Computer Science, Biomedical Engineering, Electrical Engineering, or a related quantitative field.
• 3+ to 5+ years of professional experience in data engineering, data science, or a similar role, ideally within clinical trial, healthcare, or biomedical industry.
• Strong proficiency in Python (Pandas, NumPy, software development best practices).
• Proficiency in SQL for data manipulation and querying.
• Hands-on experience with cloud platforms (e.g., AWS).
• Experience working with high-volume, complex, and time-series data (e.g., raw sensor data, device logs, patient activity).

Nice to have:

• Familiarity with clinical trial processes, ICH-GCP guidelines, and data standards (e.g., CDISC).
• Knowledge of data visualization tools (Plotly Dash, Power BI).
• Understanding of digital biomarker collection methodologies (e.g., actigraphy, vital signs).
• Experience with statistical analysis or machine learning development in a biomedical context.
• Prior experience in a regulated environment (e.g., HIPAA, GDPR, or 21 CFR Part 11).

• Develop and deploy operational analysis scripts (in Python/SQL) to generate real-time metrics for clinical study teams, including adherence/compliance monitoring, technical performance, and clinical operations support.
• Design and build scalable, automated data pipelines to ingest, clean, transform, and manage high-volume, time-series data from various digital health devices.
• Optimize existing data infrastructure and pipelines for performance, cost-efficiency, and reliability in a regulated environment.
• Collaborate closely with Clinical Integration, Workflows, and Digital Biomarker Scientists to define, implement, and validate operational data quality metrics.
• Develop automated reporting and dashboards to provide clinical study teams with actionable insights.
• Support the integration of operational data analysis results back into study management systems.
• Translate clinical operational needs and data quality requirements into technical specifications and production-ready data pipelines.
• Provide technical support and expertise on data flow and pipeline output to internal stakeholders and external clients.
• Document data flows, pipeline architectures, and analysis methodologies clearly and comprehensively.

We reserve the right to contact the selected candidates.