GCP Data Architect

We are seeking a highly skilled and visionary Data Architect to design, build, and optimize our next-generation cloud data platform. In this role, you will bridge the gap between complex clinical data ecosystems and scalable, high-performance cloud architecture. You will be responsible for defining robust ingestion patterns, architecting sophisticated data transformation layers, and ensuring the platform is secure, cost-efficient, and compliant with industry standards.

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  Data Architecture & Strategy: Design and implement scalable, secure, and cost-effective cloud data platforms, ensuring high availability and alignment with business objectives.

  
  


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  Data Transformation & Modeling: Architect robust data transformation layers using dbt (staging, intermediate, marts). Enforce rigorous testing, comprehensive documentation, reusable macros, and automated CI/CD deployment pipelines.

  
  


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  Ingestion & Orchestration: Design enterprise-grade ingestion and orchestration workflows within Matillion, incorporating advanced job orchestration, parameterization, strict error handling, and audit logging.

  
  


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  Workflow Integration: Seamlessly integrate dbt and Matillion pipelines with Cloud Composer (Apache Airflow) and Git-based version control workflows.

  
  


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  DevOps & Governance: Lead Git-based development workflows, conducting thorough code reviews, defining branching strategies, and managing CI/CD automation via Cloud Build, GitHub Actions, or GitLab CI.

  
  

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  Cloud Architecture: Proven expertise in cloud data architecture, with deep, demonstrable technical depth in Google Cloud Platform (GCP) and BigQuery.

  
  


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  Data Transformation & Ingestion: Hands-on mastery of dbt (Core/Cloud) and advanced expertise utilizing Matillion ETL for complex orchestration and ingestion patterns.

  
  


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  Core Engineering: Advanced proficiency in SQL and Python tailored for data engineering, automation, and data validation.

  
  


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  Clinical Domain Expertise: Solid understanding of clinical data standards, including CDISC SDTM/ADaM, OMOP, and HL7/FHIR. Practical experience handling data from EHR/EMR, EDC/CTMS, insurance claims, and laboratory systems.