Clinical Life Science Data Hub Functional Architect

Job Title: Clinical Life Science Data Hub Functional Architect

Location: 100% Remote

Rate: $70/hr on 1099 or C2C

Visa: H1B,L2EAD,-EAD

Experience: 15+ Years Overall | 5+ Years in Life Sciences / Clinical Trial Data

Position Overview

MiniMed is seeking a visionary Functional Architect to design, build, and govern a Clinical Life Science Data Hub on Databricks. This role sits at the intersection of clinical domain expertise and modern data engineering and is responsible for defining the end-to-end technical and functional architecture that unifies clinical trial data from EDC, CTMS, eTMF, ePRO, eConsent, safety, and device systems into a single, governed, analytics-ready platform.

The Functional Architect will serve as the primary technical authority for the Clinical Data Hub, driving the architectural vision, data modeling standards, integration design, and platform governance while ensuring outputs meet regulatory compliance, data integrity, and scientific rigor requirements for a medical device clinical environment.

Key Responsibilities

• Define and own the end-to-end functional and technical architecture of the Clinical Life Science Data Hub on Databricks using Lakehouse architecture.
• Design Medallion Architecture (Bronze / Silver / Gold) to ingest, transform, and serve clinical data across source systems.
• Architect scalable data pipelines using Apache Spark, Delta Lake, and Databricks Workflows for batch and streaming clinical data ingestion.
• Design Unity Catalog governance structures including data lineage, access controls, tagging, and metadata management.
• Define clinical data models and canonical data structures aligned to CDISC standards including CDASH, SDTM, and ADaM.
• Lead API-based and file-based integrations with EDC, CTMS, ePRO, eConsent, safety systems, device data platforms, and real-world data sources.
• Architect HL7/FHIR-compliant data exchange patterns for healthcare interoperability and device telemetry feeds.
• Design data quality frameworks including automated validation rules, reconciliation checks, and data completeness monitoring.
• Ensure the Data Hub architecture addresses 21 CFR Part 11, GDPR, HIPAA, ICH E6 R2/R3 Google Cloud Platform, and ISO 14155 requirements.
• Define audit trail mechanisms, data versioning, and immutable logging within Databricks.
• Architect Computer System Validation (CSV) strategy including IQ/OQ/PQ documentation, system risk assessments, and validation lifecycle management.
• Design RBAC, data masking, and anonymization strategies for sensitive clinical and patient data.
• Support data architecture requirements for FDA, EMA, and Notified Body regulatory submissions and inspection readiness.
• Define data marts, aggregated tables, and reusable feature stores supporting Power BI, Tableau, and Databricks SQL.
• Establish data publishing patterns and semantic layer standards using Databricks SQL, dbt, or equivalent.
• Define data SLA frameworks and freshness requirements for near-real-time and scheduled clinical reporting.
• Maintain the Clinical Data Hub Architecture Blueprint, including data flow diagrams, system integration maps, data dictionaries, and ADRs.
• Define data stewardship responsibilities and operating models across Clinical Operations, Data Management, Biostatistics, Regulatory Affairs, and IT.
• Act as the technical bridge between clinical domain stakeholders and data engineering teams.
• Engage technology vendors and third-party data providers to align integration designs and SLAs.
• Present architecture designs, platform roadmaps, and risk assessments to senior leadership and governance committees.
• Mentor data engineers and provide architectural guidance across the clinical data team.

Required Qualifications

• Bachelor's degree in Life Sciences, Computer Science, Information Systems, Biomedical Engineering, or related field.
• 10+ years of experience in data architecture or data engineering roles.
• 5+ years of experience in Life Sciences or clinical trial data environments.
• Hands-on expertise with Databricks Lakehouse, Delta Lake, Unity Catalog, Databricks Workflows, and Databricks SQL.
• Proficiency in CDISC standards, including CDASH, SDTM, and ODM.
• Understanding of HL7/FHIR and API-based clinical data integrations.
• Strong expertise in Medallion Architecture, data mesh/fabric concepts, and cloud-native data platforms across Azure, AWS, or Google Cloud Platform.
• Ability to translate complex technical architecture into clear communication for clinical and regulatory stakeholders.

Preferred Qualifications

• Databricks Certified Data Engineer Professional or Databricks Certified Associate Developer.
• Experience in diabetes, endocrinology, or medical device clinical programs.
• Expertise in architecting, designing, and implementing clinical data warehouse solutions.
• Experience with Power BI or Tableau as downstream consumers of Clinical Data Hub outputs.