Sr. Data manager/ Data architect / Data engineer lead (Medical Imaging Data)

Position Overview

Nextphase.ai is a Data Management solution provider focused on Data Operations for enterprise cloud data. We are seeking a Sr. Data Manager / Data Architect / Data Engineer Lead to join our global Image Curation and Data Products team. In this role, you will transform biomedical imaging data from clinical trials and real world sources into high-quality, FAIR datasets, ensuring stringent data quality standards and compliance while collaborating with cross-functional teams.

Key Responsibilities

• Imaging Data Pipeline Delivery: Design, implement, and maintain automated pipelines for onboarding, verifying, transforming, and curating biomedical imaging data from clinical trials and real world data sources across therapeutic areas (Oncology, Neurology, Ophthalmology) and various image file formats.
• Data Quality and Integrity: Develop solutions to detect and correct anomalies ensuring the highest data quality per industry standards (DICOM) and internal specifications (FFS, RTS, GDSR), including de-identification and PHI/PII controls.
• Data Analysis and Integration: Integrate ML and AI assisted tools into pipelines for inline image analysis, classification, and segmentation to extract and enrich metadata, optimizing overall performance.
• Image Data Management: Build and maintain large-scale catalogs of curated imaging datasets that adhere to FAIR principles, making data assets easily discoverable and accessible.
• Compliance and Controls: Ensure adherence to applicable compliance and privacy controls (GXP, CSV validations) throughout data operations.
• Collaboration: Work closely with imaging scientists, data scientists, clinical operations, and biomarker research teams to support diverse data analysis requirements.
• External Collaboration: Coordinate with external partners (e.g. CROs) to ensure incoming imaging data meets established quality standards and contractual agreements.
• Team Leadership: Lead the delivery team to ensure timely implementation of product backlog features and actively participate in agile ceremonies.

Required Qualifications

• Experience with medical imaging data and platforms (e.g. PACS, VNAs) and radiology imaging modalities (CT, PET, MRI, nifti) as well as ophthalmic imaging (OCT, FA, CFP, etc.).
• Strong understanding of DICOM standards, including metadata parsing, tags, and multi-frame images.
• Familiarity with clinical data standards (SDTM, ADaM) and integration of imaging data with tabular clinical datasets.
• Proven experience in de-identification methodologies, PHI/PII detection, and implementation of privacy controls.
• Knowledge of GXP and CSV validation frameworks.
• Proficiency in Python and related libraries (pandas, pydicom, SimpleITK, dicom-numpy, dcm2niix) along with hands-on experience in ETL/ELT processes for large imaging datasets.
• Familiarity with orchestration tools (Apache Airflow, Spark, Talend or similar), SQL/NoSQL databases (PostgreSQL, MongoDB), and image metadata stores.
• Experience with AWS infrastructure data services (RDS, Athena, Glue, EC2, Lambda, S3), containerization (Docker, HPC), and orchestration (EKS).
• Experience in data analysis and report generation tools (e.g. Tibco, Tableau, AWS QuickSight) and familiarity with DevOps tools (Git, Gitlab, Jenkins, Terraform).
• Experience with ML workflows for computer vision tasks (segmentation, classification); exposure to NLP and GenAI is a plus.
• Proven leadership skills with the ability to mentor agile team members and work effectively in cross-functional, global teams.
• Minimum of 10+ years of experience with data platforms, analysis, and insights.

Equal Opportunity Employer

Applicants must be authorized to work for any employer in the U.S. (We are unable to sponsor or take over sponsorship for employment visas).

Nextphase.ai is an equal opportunity employer. All qualified applicants will receive consideration without regard to race, color, religion, sex, national origin, disability, or any other protected characteristic.