Director, Clinical Data Management & Engineering

Summary

Join Karius, a life science startup, as their Director of Clinical Data Management & Engineering. You will lead the design and implementation of compliant, scalable processes for clinical data. This role involves managing and operationalizing clinical data for primary and secondary analysis, working within enterprise infrastructure and governance frameworks. You will contribute to Karius' enterprise-wide data platform, integrating data from various sources. The ideal candidate will have experience in supporting data analysis and visualization, collaborating with statisticians and clinical scientists. This position may include operational oversight of the Biostatistics team. Karius offers the opportunity to see a direct impact on people's lives through innovative genomic sequencing and machine learning.

Requirements

• Minimum Bachelor’s degree in a relevant field such as clinical informatics, data management, science, bioengineering, computer science, or life sciences and or life sciences and 8-10 years of experience in clinical data management, clinical informatics, data engineering, or related roles in biotech, diagnostics, or healthcare
• Proven knowledge of clinical data management process and clinical database systems
• Proven ability to design and implement clinical data infrastructure, with a focus on pipeline development, metadata management, and quality control processes
• Demonstrated experience with clinical systems and data types, including EDC, LIMS, ePRO, and associated regulatory frameworks (GCP, HIPAA, 21 CFR Part 11)
• Proficiency in SQL and Python, with experience developing or managing ETL workflows using tools like Airflow, dbt, or equivalent
• Hands-on experience working in cloud environments (AWS, GCP, or Azure) for data engineering and storage solutions
• Familiarity with data governance, access control models, and SOP development in regulated settings
• Strong written and verbal communication skills, with ability to work across clinical, regulatory, and technical teams
• Travel required up to 30% for onsite team meetings
• Subject to extended periods of sitting and/or standing, vision to monitor and moderate noise levels. Work is generally performed in an office, lab or clinical environment

Responsibilities

• Oversee, manage and optimize all aspects of the data management process for clinical trials and collaborations
• Develop and implement data management strategies and procedures to ensure accuracy, completeness, and timeliness of data
• Collaborate with cross-functional teams to define and implement data standards and processes
• Conduct regular quality checks and audits to ensure data integrity and compliance with regulatory requirements
• Identify and analyze data trends to improve data management processes and drive efficiency
• Manage and prioritize multiple projects, ensuring timely completion and delivery of high-quality data
• Design and operationalize clinical data workflows to support study operations, regulatory readiness, and long-term reusability of data
• Collaborate with the Engineering and Information Security & Compliance teams to define and enforce SOPs for clinical data ingestion, transformation, secure storage, access, and handoff, ensuring GCP and HIPAA compliance
• Manage data pipelines and integrations from EDC, LIMS, ePRO, and lab systems; ensure interoperability with downstream analysis environments (e.g., R, SAS)
• Partner with Clinical Development, Computational Biology and Bioinformatics, Engineering, and Information Security & Compliance to ensure data is audit-ready and analysis-ready
• Act as a core stakeholder in the cross-functional data platform program, supporting ingestion and structuring of clinical, medical and real-world data as needed
• Support ad hoc data analyses and dashboard development for clinical program insights and cross-functional metrics tracking
• Document and catalog metadata, enabling structured data access for internal and external partners
• May provide operational oversight of Biostatistics team structure and resourcing depending on candidate experience and organizational evolution

Preferred Qualifications

• Master’s or PhD preferred. Masters requires 6 years of experience; PhD requires 4 years of experience in clinical data management, clinical informatics, data engineering, or related roles in biotech, diagnostics, or healthcare
• Experience supporting or conducting clinical data analysis, including exploratory statistics or data visualization using tools like R, SAS, Tableau, or Python preferred
• Exposure to commercial or real-world data sources, such as CRM (e.g., Salesforce), diagnostic pipeline data, or customer reporting systems
• Knowledge of CDISC standards (SDTM, ADaM) and experience preparing datasets for regulatory submissions
• Experience in a fast-paced, cross-functional environment, preferably in a startup or high growth-stage biotech company
• High level of professionalism, integrity, and commitment to achieving results
• Ability to thrive in a dynamic and rapidly evolving environment
• Strong organizational skills and attention to detail
• Passion for contributing to the company’s success and supporting its mission to advance diagnostic technologies

Benefits

• $207,933 - $311,899 a year
• (Compensation offerings will be based on the candidate's geographic location)
• Hybrid or Remote (USA)