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Senior Google Data (AI) Architect
<div><strong><b>Description</b></strong><br/><br/><b>Job Description Summary</b><br/><br/>We are seeking an exceptional Senior Google Cloud Data Architect who is passionate about building world class, cloud native <b>data platforms and data services</b> that power the enterprise.<br/><br/>This is not a generic architect role - it is a high influence, high ownership opportunity to help define how a modern financial institution designs, scales, and operates <b>data platforms on Google Cloud</b>, with a strong focus on enabling <b>data as a product and data as a service</b> capabilities.<br/><br/>You will play a key role in evolving our platforms to support not only analytics and operational workloads, but also <b>emerging AI and intelligent application patterns</b> that depend on high-quality, well-governed, and accessible data.<br/><br/>If you're excited by complex engineering challenges, modern GCP data capabilities, and shaping how <b>data platforms evolve to support the next generation of intelligent systems</b>, we want to meet you.<br/><br/><b>Job Description</b><br/><br/>Join us as a Senior Google Data Architect and help shape the future of our <b>enterprise data services ecosystem</b>. In this high impact role, you'll leverage Google Cloud to design and deliver <b>scalable, secure, and reusable data platforms and APIs</b> that fuel analytics, real-time processing, and enterprise integration.<br/><br/>You will define how data is <b>ingested, processed, governed, and exposed</b> across the organization, enabling consistent and reliable access to trusted data.<br/><br/>In parallel, you will help extend these platforms to support <b>AI/ML and emerging agent-driven use cases</b>, ensuring our data foundation is fully prepared to power intelligent applications and automated decisioning in a controlled, enterprise-ready manner.<br/><br/><b>Job Description Details:</b><br/><br/><ul><li>Define and evolve target-state <b>data platform and data services architecture</b> aligned to business strategy and modernization goals</li><li>Establish enterprise standards and reference architectures for <b>data as a service, event-driven architecture, and API-based data access</b></li><li>Drive adoption of <b>data as a strategic asset</b>, enabling operational, analytical, and intelligent system use cases across the enterprise</li><li>Architect scalable <b>data platforms that support both traditional workloads and emerging AI/ML use cases</b>, grounded in trusted enterprise data</li><li>Define integration patterns that unify <b>data services, APIs, and AI capabilities</b> to enable intelligent applications and automation</li><li>Enable <b>data accessibility, reuse, and contextualization</b> to support cross-platform consumption, including emerging agent-driven workflows</li><li>Establish foundational patterns for <b>data retrieval, context enrichment, and grounding</b> to support advanced use cases such as AI and real-time decisioning</li><li>Architect and design <b>enterprise-grade data pipelines</b> supporting batch, streaming, and real-time workloads</li><li>Build and standardize <b>data ingestion, transformation, and distribution frameworks</b> that power scalable data services capabilities</li><li>Ensure delivery of <b>high-quality, governed, and trusted data pipelines</b> that support analytics, APIs, and downstream intelligent applications</li><li>Implement best practices for <b>event-driven data movement and microservices-based integration patterns</b></li><li>Design <b>data models and structures</b> that enable data productization and consumption across analytics, APIs, and AI-driven use cases</li><li>Architect <b>high-performance storage solutions</b> (including Bigtable, Spanner and other GCP services) to meet throughput, latency, and scalability requirements</li><li>Enable <b>secure, governed, and efficient data access patterns</b> across operational, analytical, and real-time environments</li><li>Serve as a <b>trusted advisor and technical leader</b>, mentoring teams, driving best practices, and partnering with stakeholders to identify high-value data and AI-enabled use cases</li></ul><br/><br/><b>Required Qualifications</b><br/><ul><li><b>Job Description Summary</b><br/><br/>We are seeking an exceptional Senior Google Cloud Data Architect who is passionate about building world class, cloud native <b>data platforms and data services</b> that power the enterprise.<br/><br/>This is not a generic architect role - it is a high influence, high ownership opportunity to help define how a modern financial institution designs, scales, and operates <b>data platforms on Google Cloud</b>, with a strong focus on enabling <b>data as a product and data as a service</b> capabilities.<br/><br/>You will play a key role in evolving our platforms to support not only analytics and operational workloads, but also <b>emerging AI and intelligent application patterns</b> that depend on high-quality, well-governed, and accessible data.<br/><br/>If you're excited by complex engineering challenges, modern GCP data capabilities, and shaping how <b>data platforms evolve to support the next generation of intelligent systems</b>, we want to meet you.<br/><br/><b>Job Description</b><br/><br/>Join us as a Senior Google Data Architect and help shape the future of our <b>enterprise data services ecosystem</b>. In this high impact role, you'll leverage Google Cloud to design and deliver <b>scalable, secure, and reusable data platforms and APIs</b> that fuel analytics, real-time processing, and enterprise integration.<br/><br/>You will define how data is <b>ingested, processed, governed, and exposed</b> across the organization, enabling consistent and reliable access to trusted data.<br/><br/>In parallel, you will help extend these platforms to support <b>AI/ML and emerging agent-driven use cases</b>, ensuring our data foundation is fully prepared to power intelligent applications and automated decisioning in a controlled, enterprise-ready manner.<br/><br/><b>Job Description Details:</b><br/><br/><ul><li>Define and evolve target-state <b>data platform and data services architecture</b> aligned to business strategy and modernization goals</li><li>Establish enterprise standards and reference architectures for <b>data as a service, event-driven architecture, and API-based data access</b></li><li>Drive adoption of <b>data as a strategic asset</b>, enabling operational, analytical, and intelligent system use cases across the enterprise</li><li>Architect scalable <b>data platforms that support both traditional workloads and emerging AI/ML use cases</b>, grounded in trusted enterprise data</li><li>Define integration patterns that unify <b>data services, APIs, and AI capabilities</b> to enable intelligent applications and automation</li><li>Enable <b>data accessibility, reuse, and contextualization</b> to support cross-platform consumption, including emerging agent-driven workflows</li><li>Establish foundational patterns for <b>data retrieval, context enrichment, and grounding</b> to support advanced use cases such as AI and real-time decisioning</li><li>Architect and design <b>enterprise-grade data pipelines</b> supporting batch, streaming, and real-time workloads</li><li>Build and standardize <b>data ingestion, transformation, and distribution frameworks</b> that power scalable data services capabilities</li><li>Ensure delivery of <b>high-quality, governed, and trusted data pipelines</b> that support analytics, APIs, and downstream intelligent applications</li><li>Implement best practices for <b>event-driven data movement and microservices-based integration patterns</b></li><li>Design <b>data models and structures</b> that enable data productization and consumption across analytics, APIs, and AI-driven use cases</li><li>Architect <b>high-performance storage solutions</b> (including Bigtable, Spanner and other GCP services) to meet throughput, latency, and scalability requirements</li><li>Enable <b>secure, governed, and efficient data access patterns</b> across operational, analytical, and real-time environments</li><li>Serve as a <b>trusted advisor and technical leader</b>, mentoring teams, driving best practices, and partnering with stakeholders to identify high-value data and AI-enabled use cases</li></ul><br/><br/><b>Basic (Required) Qualifications</b> <br/><ul><li>Minimum 7 years of experience in data architecture, cloud data engineering, or enterprise data platform design.</li><li>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<ul><li>Strong experience designing large scale data models for operational workloads.</li><li>Proven ability to build resilient, scalable pipelines for high volume batch and streaming data.</li><li>Proficiency in SQL and experience with Python or Java for data engineering pipelines.</li><li>Strong understanding of distributed systems, workflow orchestration, real time analytics, and event-driven design.</li><li>Experience designing secure, governed, production grade cloud architectures.</li></ul></li><li>Excellent communication skills with the ability to simplify complexity and influence decision makers.</li></ul><br/><br/><b>Preferred Qualifications</b></li><li>Experience with enterprise financial services, payments, or transaction heavy domains. </li><li>Background in API first design, microservices, and federated data architectures. </li><li>Familiarity with data governance frameworks, lineage, cataloging tools, or metadata platforms. </li><li>Experience with DevOps, CI/CD, IaC (Terraform), or platform engineering concepts. </li><li>Certification: Professional Data Engineer or Professional Cloud Architect (GCP).</li></ul><br/><br/><b>Exempt Status: (Yes</b> = not eligible for overtime pay) (<b>No</b> = eligible for overtime pay)<br/>Yes<br/><br/><b>Workplace Type:</b><br/>Office<br/><br/>Our Approach to <b>Office </b>Workplace Type<br/><br/>Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.<br/><br/><b>Compensation Range:</b><br/>Total Base Pay Range 93,000.00 - 189,000.00 USD Annual<br/><br/>The compensation range represents the anticipated low and high end of the base compensation range for this position. Actual compensation will vary based on various factors including but not limited to location, experience, and education. Colleagues in this position are also eligible to participate in an applicable incentive compensation plan. In addition, Huntington provides a variety of benefits to colleagues, including health insurance coverage, wellness program, life and disability insurance, retirement savings plan, paid leave programs, paid holidays and paid time off (PTO). <br/><br/></div>
