Clinical Data Engineering Lead
Novartis
3 months ago
On-site
Cambridge, MA
$176,400 - $327,600 USD yearly
Clinical Research and Development
Key responsibilities:
- Define and implement the clinical data engineering roadmap aligned with Novartis’ data and digital strategy, collaborating with SMEs and OncDS leadership.
- Integrate advanced tools and AI/ML-ready infrastructure to support predictive modeling, multimodal analytics, and real-world data applications.
- Align clinical and pre-clinical data engineering initiatives with the broader oncology strategy.
- Lead, manage, and develop a high-performing clinical data engineering team.
- Drive strategic initiatives and partnerships across a matrixed organization.
- Oversee data ingestion, transformation, and validation for clinical trial data, ensuring compliance with GCP/GxP, CDISC, and SOPs.
- Collaborate with CROs and internal teams to optimize data flow, versioning, and retention policies.
- Build and optimize data pipelines for structured and unstructured clinical data to enable advanced analytics.
- Deploy scalable solutions for data harmonization, metadata management, and interoperability across Foundry, Domino, Snowflake, and POSIT Connect.
- Develop and manage applications and visualization tools to create novel data products for clinical decision-making and AI-driven oncology initiatives.
Essential requirements:
- Onsite in Cambridge, MA; not remote; 0–3% travel.
- Master’s degree in computer science, Bioinformatics, Data Engineering, Software Engineering, or related field; PhD preferred.
- 10+ years of hands-on experience architecting/managing clinical data engineering, data management, and bioinformatics solutions in pharma/biotech.
- Expertise designing, implementing, and scaling data infrastructure for clinical development, including AI/ML-driven analytics and multimodal integration.
- Ability to define/document/operationalize end-to-end assay data generation and processing pipelines (automation, orchestration, compliance).
- Oncology clinical trials experience, including regulatory-compliant biomarker data management and CDISC standards (CDISC, SDTM, ADaM).
- Familiarity with FAIR principles, data harmonization, and enterprise data governance.
- Strong leadership and stakeholder management skills.
Desirable requirements:
- Experience leading cross-functional oncology data science initiatives (translational science, biomarker analysis, real-world data, exploratory clinical research); NGS and modern bioinformatics tools.
- Cloud-native architectures, data lakes, visualization (e.g., RShiny, Dash, Spotfire); programming/engineering (R, Python, Java, shell scripting, Linux, HPC); knowledge of GxP, Agile, AI/ML operations, and AI agents.
Benefits and compensation (as stated):
- Salary range: $176,400–$327,600/year.
- Performance-based cash incentive; eligibility for annual equity awards (depending on level).
- US-based eligible employees: health/life/disability benefits, 401(k) with company contribution and match, and time off (vacation, personal days, holidays, other leaves).
- Define and implement the clinical data engineering roadmap aligned with Novartis’ data and digital strategy, collaborating with SMEs and OncDS leadership.
- Integrate advanced tools and AI/ML-ready infrastructure to support predictive modeling, multimodal analytics, and real-world data applications.
- Align clinical and pre-clinical data engineering initiatives with the broader oncology strategy.
- Lead, manage, and develop a high-performing clinical data engineering team.
- Drive strategic initiatives and partnerships across a matrixed organization.
- Oversee data ingestion, transformation, and validation for clinical trial data, ensuring compliance with GCP/GxP, CDISC, and SOPs.
- Collaborate with CROs and internal teams to optimize data flow, versioning, and retention policies.
- Build and optimize data pipelines for structured and unstructured clinical data to enable advanced analytics.
- Deploy scalable solutions for data harmonization, metadata management, and interoperability across Foundry, Domino, Snowflake, and POSIT Connect.
- Develop and manage applications and visualization tools to create novel data products for clinical decision-making and AI-driven oncology initiatives.
Essential requirements:
- Onsite in Cambridge, MA; not remote; 0–3% travel.
- Master’s degree in computer science, Bioinformatics, Data Engineering, Software Engineering, or related field; PhD preferred.
- 10+ years of hands-on experience architecting/managing clinical data engineering, data management, and bioinformatics solutions in pharma/biotech.
- Expertise designing, implementing, and scaling data infrastructure for clinical development, including AI/ML-driven analytics and multimodal integration.
- Ability to define/document/operationalize end-to-end assay data generation and processing pipelines (automation, orchestration, compliance).
- Oncology clinical trials experience, including regulatory-compliant biomarker data management and CDISC standards (CDISC, SDTM, ADaM).
- Familiarity with FAIR principles, data harmonization, and enterprise data governance.
- Strong leadership and stakeholder management skills.
Desirable requirements:
- Experience leading cross-functional oncology data science initiatives (translational science, biomarker analysis, real-world data, exploratory clinical research); NGS and modern bioinformatics tools.
- Cloud-native architectures, data lakes, visualization (e.g., RShiny, Dash, Spotfire); programming/engineering (R, Python, Java, shell scripting, Linux, HPC); knowledge of GxP, Agile, AI/ML operations, and AI agents.
Benefits and compensation (as stated):
- Salary range: $176,400–$327,600/year.
- Performance-based cash incentive; eligibility for annual equity awards (depending on level).
- US-based eligible employees: health/life/disability benefits, 401(k) with company contribution and match, and time off (vacation, personal days, holidays, other leaves).