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About the Role

This high-influence, high-ownership role defines how a modern financial institution designs, scales, and operates data platforms on Google Cloud, focusing on data as a product and service. The Senior Google Cloud Data Architect will evolve platforms to support analytics, operational workloads, and emerging AI/intelligent application patterns, ensuring high-quality, governed, and accessible data. The role involves designing and delivering scalable, secure, and reusable data platforms and APIs for analytics, real-time processing, and enterprise integration, defining data ingestion, processing, governance, and exposure. It also extends platforms to support AI/ML and agent-driven use cases for intelligent applications and automated decisioning.

Responsibilities

Define and evolve target-state data platform and data services architecture aligned to business strategy and modernization goals
Establish enterprise standards and reference architectures for data as a service, event-driven architecture, and API-based data access
Drive adoption of data as a strategic asset, enabling operational, analytical, and intelligent system use cases across the enterprise
Architect scalable data platforms that support both traditional workloads and emerging AI/ML use cases, grounded in trusted enterprise data
Define integration patterns that unify data services, APIs, and AI capabilities to enable intelligent applications and automation
Enable data accessibility, reuse, and contextualization to support cross-platform consumption, including emerging agent-driven workflows
Establish foundational patterns for data retrieval, context enrichment, and grounding to support advanced use cases such as AI and real-time decisioning
Architect and design enterprise-grade data pipelines supporting batch, streaming, and real-time workloads
Build and standardize data ingestion, transformation, and distribution frameworks that power scalable data services capabilities
Ensure delivery of high-quality, governed, and trusted data pipelines that support analytics, APIs, and downstream intelligent applications
Implement best practices for event-driven data movement and microservices-based integration patterns
Design data models and structures that enable data productization and consumption across analytics, APIs, and AI-driven use cases
Architect high-performance storage solutions (including Bigtable, Spanner and other GCP services) to meet throughput, latency, and scalability requirements
Enable secure, governed, and efficient data access patterns across operational, analytical, and real-time environments
Serve as a trusted advisor and technical leader, mentoring teams, driving best practices, and partnering with stakeholders to identify high-value data and AI-enabled use cases

Requirements

Minimum 7 years of experience in data architecture, cloud data engineering, or enterprise data platform design
Deep hands-on expertise with multiple GCP services, including BigQuery, Bigtable, Pub/Sub, Dataflow (Beam), Cloud Composer, GKE, Apigee, Cloud Storage, Gemini Enterprise Agent Platform
Strong experience designing large scale data models for operational workloads
Proven ability to build resilient, scalable pipelines for high volume batch and streaming data
Proficiency in SQL
Experience with Python or Java for data engineering pipelines
Strong understanding of distributed systems, workflow orchestration, real time analytics, and event-driven design
Experience designing secure, governed, production grade cloud architectures
Excellent communication skills with the ability to simplify complexity and influence decision makers
Experience with enterprise financial services, payments, or transaction heavy domains (preferred)
Background in API first design, microservices, and federated data architectures (preferred)
Familiarity with data governance frameworks, lineage, cataloging tools, or metadata platforms (preferred)
Experience with DevOps, CI/CD, IaC (Terraform), or platform engineering concepts (preferred)

Skills

Data Architecture
Cloud Data Engineering
Enterprise Data Platform Design
Google Cloud Platform (GCP)
BigQuery
Bigtable
Pub/Sub
Dataflow (Beam)
Cloud Composer
GKE
Apigee
Cloud Storage
Gemini Enterprise Agent Platform
Large Scale Data Modeling
Resilient Data Pipelines
Scalable Data Pipelines
Batch Data Processing
Streaming Data Processing
SQL
Python
Java
Distributed Systems
Workflow Orchestration
Real-time Analytics
Event-driven Design
Secure Cloud Architecture
Governed Cloud Architecture
Production-grade Cloud Architecture
Communication
Influencing Decision Makers
Financial Services
Payments
API First Design
Microservices
Federated Data Architectures
Data Governance Frameworks
Data Lineage
Data Cataloging Tools
Metadata Platforms
DevOps
CI/CD
Infrastructure as Code (IaC)
Terraform
Platform Engineering

Work Type

Full-time
Onsite

Experience Level

Senior level
Minimum 7 years of experience in data architecture, cloud data engineering, or enterprise data platform design

Education Level

Professional Data Engineer (GCP) certification (preferred)
Professional Cloud Architect (GCP) certification (preferred)

Salary/Compensations

93,000.00 - 189,000.00 USD Annual

Benefits

Health insurance coverage
Wellness program
Life and disability insurance
Retirement savings plan
Paid leave programs
Paid holidays
Paid time off (PTO)

About the Company

Huntington aims to make people's lives better by reinventing banking and fostering a strong internal culture.
The company values a Can-Do Attitude, Service Heart, and Forward Thinking.
Huntington focuses on doing right by people and impacting lives positively.

Equal Opportunity

Huntington is an Equal Opportunity Employer.
The company is committed to site accessibility and provides reasonable accommodations for job applicants or employees to perform essential job functions.