Data Architect - Health Care/Life Sciences| GCP · Matillion · DBT - Remote Contract Position

Role Overview We are seeking an experienced Data Architect with deep, hands-on expertise in GCP BigQuery, Matillion ETL, and dbt (Core/Cloud). You will lead the design and delivery of cloud-native, scalable data platforms for clinical and life-sciences clients, establishing architecture patterns that span ingestion, transformation, governance, and analytics. This is a senior individual-contributor and technical-lead role with high visibility into client delivery and pre-sales solutioning. Core Technology Stack Cloud Platform : GCP · BigQuery · Cloud Storage · Cloud Composer (Airflow) Cloud Build ETL / Orchestration : Matillion ETL · Cloud Composer · GitLab CI / GitHub Actions Transformation & Modeling: dbt Core / Cloud · Staging · Intermediate · Marts · Macros · Tests Languages: SQL (Advanced) · Python · Jinja2 Clinical Standards: CDISC SDTM/ADaM · OMOP · HL7/FHIR · EHR/EMR · EDC/CTMS DevOps & Governance: Git · Code Review · CI/CD · Data Quality · Audit Logging Key Responsibilities GCP BigQuery Architecture • Design multi-project BigQuery environments aligned to medallion architecture principles • Optimize query performance using partitioning, clustering, and materialization strategies • Enforce dataset-level IAM, column-level security, and VPC Service Controls for regulated data • Integrate BigQuery with Cloud Storage, Pub/Sub, and Vertex AI for end-to-end analytics pipelines Matillion ETL – Orchestration & Ingestion • Architect Matillion job hierarchies including orchestration jobs, transformation jobs, and reusable profiles • Implement parameterization patterns for scalable multi-source loading • Design error-handling frameworks with audit logging, retry logic, and alerting via Cloud Monitoring • Migrate and refactor legacy ETL pipelines (on-prem or Informatica) into Matillion on GCP DBT Transformation Layer • Build and govern dbt project structures: staging → intermediate → mart model layers • Author reusable macros (Jinja2), generic and singular tests, and schema.yml documentation blocks • Enforce CI/CD pipelines for dbt via GitLab CI / GitHub Actions • Connect dbt docs to DataHub, Collibra, or Alation for enterprise data governance Cloud Composer & Workflow Orchestration • Design and maintain Cloud Composer (Airflow) DAGs to coordinate Matillion jobs, dbt runs, and downstream consumers • Implement SLA monitoring, alerting, and dependency management across cross-domain pipelines DevOps & CI/CD • Manage Git branching strategies across data engineering repositories • Configure Cloud Build / GitHub Actions / GitLab CI pipelines for automated testing, linting, and deployment • Apply infrastructure-as-code (Terraform) for BigQuery datasets, Matillion instances, and IAM resources Clinical Data & Compliance • Map source EHR/EMR, EDC, CTMS, and claims data to CDISC SDTM/ADaM and OMOP CDM standards • Design HL7/FHIR-compatible ingestion pipelines for real-world evidence and interoperability use cases • Ensure platform compliance with GxP, HIPAA, 21 CFR Part 11, and SOC 2 requirements Required Qualifications • 8–14 years in data architecture, data engineering, or analytics engineering roles • 4+ years hands-on with GCP BigQuery: DDL/DML, query optimization, IAM, Data Transfer Service, BigQuery ML • 3+ years with Matillion ETL: job design, orchestration patterns, GCP connectors, Python components • 3+ years with dbt Core and/or Cloud: project structure, macros, testing, documentation, CI/CD integration • Advanced SQL proficiency: window functions, CTEs, performance tuning, and analytical patterns • Proficient in Python for data validation, automation, and custom Matillion/Airflow components • Strong Git-based workflow discipline: branching, code review, pull requests, semantic versioning Preferred Qualifications • Google Professional Data Engineer or Cloud Architect certification • Experience in clinical / pharmaceutical / life-sciences data environments (CDISC, OMOP, HL7/FHIR) • Familiarity with Terraform for GCP infrastructure provisioning • Exposure to dbt Semantic Layer, MetricFlow, or dbt Cloud Enterprise features • Experience with DataHub, Collibra, or Alation for metadata management and data cataloging Background in MDM solutions (Reltio, Informatica MDM) is a plus