Google Cloud Platform Architect Data

• We are seeking a Google Cloud Platform Lead / Architect with strong Data Engineering expertise to design and deliver secure, scalable, and cost-optimized data platforms on Google Cloud Platform (Google Cloud Platform).
• The ideal candidate will lead architecture design, data engineering initiatives, and DevOps automation while enabling advanced analytics and AI/ML capabilities.

Architecture And Solution Design:

• Lead end-to-end architecture for data platforms on Google Cloud Platform including networking, security, compute, storage, and analytics components.
• Define High-Level Design (HLD) and Low-Level Design (LLD) along with architecture standards and reference patterns.
• Drive architecture decisions balancing performance, reliability, scalability, security, and cost optimization.
• Conduct design reviews, technical audits, and architecture governance.

• Design and implement scalable pipelines for structured, semi-structured, and unstructured data using batch and streaming patterns.
• Develop and maintain ETL/ELT workflows, data models, and transformation pipelines.
• Architect and optimize BigQuery-based data warehouse/lakehouse solutions.
• Lead data warehouse design, including dimensional modeling, SCD strategies, conformed dimensions, and data quality rules.
• Implement partitioning, clustering, and query performance tuning.

• Implement and enforce security controls using IAM, service accounts, and organization policies.
• Manage and support workloads on GKE and Compute Engine with scalability and monitoring.
• Utilize Google Cloud Storage (GCS) for governed storage and lifecycle management.
• Use Dataproc for Spark/Hadoop based processing.

• Build and manage CI/CD pipelines using Git and GitHub Actions.
• Establish DevOps best practices including Git branching strategy, environment promotion, and version management.
• Implement automation standards and infrastructure governance.

• Collaborate with ML and Data Science teams to operationalize ML services using Vertex AI.
• Support ML training and inference integration with data platforms.
• Ensure compliance with AI governance, security, and audit requirements.

• 15+ years experience as Google Cloud Platform Lead / Architect with strong data engineering background.

• 6+ years experience with Google Cloud Platform services including:

• IAM, VPC, GCS, BigQuery
• Vertex AI
• GKE
• Compute Engine
• Dataproc
• GitHub Actions
• Strong expertise in data warehouse design and distributed systems.
• Experience creating HLD, LLD, and architecture standards.
• Strong experience building BigQuery-based data warehouse / lakehouse solutions.
• Experience leading data modeling and DWH design.
• Experience with DevOps, CI/CD, and automation.
• Experience building Google Cloud Platform-native data pipelines.
• AI/ML enablement experience using Vertex AI.

• Data Engineering
• Advanced SQL

• Pipeline design
• Performance tuning
• Data quality controls

• Dimensional modeling
• Distributed processing
• BigQuery optimization

• Git workflows
• GitHub Actions
• CI/CD pipeline automation
• Environment management

• Infrastructure as Code (Terraform / Google Cloud Platform Deployment Manager).
• MLOps experience including model lifecycle, CI/CD for ML, experiment tracking, deployment automation, and monitoring.
• Healthcare domain exposure.
• Experience with Medicare STAR ratings.

• Bachelor s degree in Computer Science, Engineering, or related field.

• Google Cloud Platform Certifications preferred:

  Professional Cloud Architect
• Professional Data Engineer.