GCP Architect Job Chicago area,Illinois USA,IT/Tech

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)
Big Query (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:

Dev Ops 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:

Big Query
Cloud Storage
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