Job Title: GCP Architect
Duration: 6 months Contract to hire
Location: Chicago is the preferred location, but open to candidates from anywhere in the U.S.
 

Role Overview
We are seeking a highly experienced GCP Architect to design and lead the development of enterprise-scale data and AI platforms on Google Cloud Platform (GCP). This role is responsible for defining target-state architectures, establishing best practices, and enabling scalable, secure, and high-performance data ecosystems that support analytics and AI initiatives across the enterprise.
The ideal candidate will bring deep expertise in cloud data architecture, modern lakehouse patterns, governance frameworks, and distributed data systems, along with strong leadership and stakeholder engagement skills.

Key Responsibilities
Cloud Data Platform Architecture

• Architect enterprise-scale data platforms on GCP for analytics, reporting, and AI/ML use cases.
• Design robust and scalable solutions leveraging:  

• Cloud Storage (data lakes)
• BigQuery (data warehousing/lakehouse)
• GCP-native services (Dataflow, Pub/Sub, Dataproc, etc.)

• Define reference architectures and reusable frameworks for multi-domain data ecosystems.

Data Lakehouse & Modern Architecture Design

• Design and implement modern data lake/lakehouse architectures aligned with business needs.
• Establish medallion architecture (Bronze, Silver, Gold layers) for:  
  • Data ingestion
  • Data curation
  • Transformation
  • Consumption
• Enable unified analytics and AI capabilities with optimized storage and processing layers.

Data Strategy & Platform Roadmap

• Define end-to-end data strategies including:  
  • Data integration and ingestion patterns
  • Data modeling standards (dimensional, normalized, and hybrid models)
  • Performance and cost optimization strategies
  • Platform evolution and modernization roadmaps
• Drive alignment with enterprise architecture and digital transformation goals.

Data Governance & Security Frameworks

• Establish enterprise-wide frameworks for:  

• Data governance and stewardship
• Metadata management and cataloging
• Data lineage and traceability
• Data quality management

• Design secure architectures using IAM, encryption, data masking, and access control policies.
• Ensure compliance with regulatory and organizational standards.

Scalable Data Processing Architectures

• Guide the design of batch, streaming, and real-time data pipelines across business domains.
• Enable event-driven architectures using Pub/Sub and streaming frameworks.
• Support AI-ready data ecosystems with optimized data pipelines for ML consumption.

Cross-Functional Leadership & Collaboration

• Partner with:  
  • Engineering teams to implement architecture patterns
  • Data scientists to enable AI/ML workflows

• • Business and leadership teams to align on data strategy
  • Act as a trusted advisor to stakeholders on data platform decisions.
• Provide mentorship and technical leadership across teams.

Best Practices & Standards

• Drive adoption of best practices for:  

• Scalability and performance optimization
• Resilience and fault tolerance
• Reusable and modular architecture design

Promote standards in:  

• • DevOps and CI/CD for data platforms
  • Infrastructure as Code (IaC)
  • Documentation and knowledge sharing

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 10+ years of experience in data engineering, data architecture, or cloud architecture.
• Must have GCP certification (e.g., Professional Cloud Architect)
• Proven experience designing enterprise-scale data platforms on GCP.
• Deep expertise in:  o   BigQuery o      Cloud Storage o Dataflow / Pub/Sub
• Strong understanding of modern data architectures (lakehouse, data mesh, medallion).
• Experience with data governance, security, and compliance frameworks.

Preferred Skills

• Experience with multi-cloud or hybrid cloud architectures.
• Familiarity with AI/ML platforms (Vertex AI) and ML data pipelines.
• Knowledge of ETL/ELT tools (dbt, Dataform, Talend).
• Experience with streaming technologies and real-time analytics.
• Hands-on experience with Infrastructure as Code (Terraform, Deployment Manager).
• Understanding of data mesh and domain-oriented data architectures.

Key Competencies

• Strategic thinking and architectural vision
• Strong leadership and stakeholder management skills
• Excellent problem-solving and decision-making abilities
• Ability to translate business needs into scalable technical architectures
• Strong communication and documentation skills