GCP Data Engineer

Quantiphi is an award-winning Applied AI and Big Data software and services company, recognized for its innovative approach and rapid growth. The Senior Data Architect will be responsible for designing and maintaining scalable data pipelines and ensuring data architecture aligns with best practices on GCP.

Responsibilities:

• Define and own the overall data architecture for ingestion, storage, transformation, and analytics on GCP (focused on BigQuery and Cloud Composer)
• Design data modeling frameworks and best practices for structured and semi-structured insurance data (Policy, Claims, Billing)
• Collaborate with Business Analysts to translate functional Guidewire requirements into conceptual and logical data models
• Work with Data Modelers and Data Engineers to define physical schemas, transformation strategies, and data lineage standards
• Design and oversee data ingestion architecture from Guidewire (staging, raw, curated layers) using SQL-based ELT pipelines
• Establish data governance, metadata management, and data quality frameworks for transparency and compliance
• Review and optimize BigQuery data structures (partitioning, clustering, query tuning, storage tiering)
• Define naming conventions, security models (IAM/RLS), and access control standards for the data warehouse
• Ensure architecture alignment with cloud best practices for scalability, cost optimization, and maintainability
• Provide architectural direction and mentorship to the Data Engineering Lead, Data Modeler, and Data Engineers
• Partner with enterprise security and infrastructure teams to maintain compliance with data privacy regulations

Requirements:

• 8+ years of experience in data architecture/design with at least 6+ years on GCP
• Deep expertise in Google BigQuery data warehouse design and performance tuning
• Strong working knowledge of Cloud Composer (Airflow) and orchestration pipelines
• Solid understanding of insurance data structures, preferably from Guidewire systems (PolicyCenter, BillingCenter, ClaimsCenter)
• Experience architecting enterprise-grade ELT frameworks and multi-layered data architectures (staging → raw → curated → analytics)
• Hands-on proficiency in SQL and schema design for analytical environments (star/snowflake models)
• Familiarity with data governance, cataloging, and metadata management
• Ability to lead technical teams and guide design decisions with both functional and technical stakeholders