GCP Architect (RARR Job 6468)

We are seeking an experienced GCP Data Architect to join the AMS & Development team of a leading multinational FMCG organization. This role is responsible for designing, governing, and evolving enterprise-scale data platforms on Google Cloud Platform (GCP) to enable scalable, high-performance analytics and data-driven decision-making. The ideal candidate will work in a cloud-first environment, leveraging GCP and hyperscaler technologies to build modern data lakehouse architectures, real-time analytics platforms, and AI-ready data ecosystems. The role combines strategic architecture, hands-on solution design, and production support leadership to ensure continuous innovation and operational excellence across enterprise data platforms. Key Responsibilities

• Enterprise Data Architecture
  • Define and implement enterprise data architecture aligned with business objectives.
  • Design scalable and secure architectures for:
    • Data Lakes
    • Data Warehouses
    • Lakehouse platforms
    • Batch and Real-Time Data Processing
  • Establish enterprise standards for:
    • Data Modeling
    • Data Integration
    • Data Governance
    • Data Quality
• GCP Data Platform Architecture
  • Design and implement cloud-native data solutions using GCP services, including:
    • BigQuery
    • Cloud Storage
    • Dataflow
    • Dataproc
    • Pub/Sub
    • Cloud Composer
  • Build highly scalable, resilient, and high-performance data platforms.
  • Optimize GCP services for data ingestion, transformation, analytics, and reporting.
• Data Pipeline & Integration
  • Design and oversee robust ETL/ELT pipelines for data ingestion from:
    • ERP Systems
    • CRM Applications
    • External and Third-Party Data Sources
  • Enable both batch and real-time streaming architectures.
  • Ensure:
    • Reliable orchestration
    • Pipeline monitoring
    • Error handling and recovery
    • Data quality validation
• AMS & Production Support Leadership
  • Provide architectural governance for production data platforms.
  • Lead and support:
    • Production incident resolution
    • Root Cause Analysis (RCA)
    • Data pipeline troubleshooting
  • Ensure:
    • High availability
    • Platform resilience
    • Business continuity
    • SLA compliance
  • Govern production releases, enhancements, and deployment validation.
• Data Modeling & Governance
  • Design conceptual, logical, and physical data models.
  • Implement enterprise data governance practices, including:
    • Metadata Management
    • Data Lineage
    • Data Cataloging
  • Ensure compliance with:
    • Data Security
    • Privacy Regulations
    • Access Control Policies
• Analytics Enablement
  • Enable trusted data consumption for:
    • Business Intelligence (BI)
    • Advanced Analytics
    • AI/ML Solutions
  • Support reporting platforms including:
    • Looker