Senior Google Data Architect

Huntington National Bank•Columbus, OH

23h•Hybrid

About The Position

Join us as a Google Data Architect Senior and help shape the future of our enterprise data ecosystem. In this high‑impact role, you’ll leverage the full power of the Google Cloud Platform (GCP) to design and deliver modern, scalable, and secure data solutions that fuel analytics, real‑time intelligence, and digital transformation across the organization. As a senior technical leader, you’ll collaborate closely with engineering, product, and business partners to define target‑state data architectures and bring them to life using GCP’s modern data stack—including BigQuery, Pub/Sub, Dataflow, Cloud Composer, Apigee, GKE, and Google Cloud Bigtable for high‑throughput, low‑latency workloads. You will translate complex business requirements into elegant end‑to‑end architecture patterns spanning data ingestion, transformation, storage, integration, and governance. Your work will directly influence the scalability, reliability, and strategic value of our data platforms while advancing the organization’s enterprise data strategy. Architect modern, cloud‑native data solutions using GCP’s advanced analytics and data engineering services. Design resilient pipelines and ingestion frameworks that support batch, streaming, and real‑time workloads. Apply best‑practice data modeling across conceptual, logical, and physical layers to support both operational and analytical use cases. Lead solution design for Bigtable‑based, high‑velocity operational data platforms. Collaborate with cross‑functional teams to define standards, patterns, and reusable frameworks that accelerate delivery. Champion secure‑by‑design practices, performance optimization, observability, and governance across all data solutions. Influence enterprise data strategy and help guide the evolution of our cloud data ecosystem. Enterprise Data Modeling & Architecture Design conceptual, logical, and physical data models supporting analytical and operational use cases, aligned with Huntington’s enterprise data architecture patterns. High‑Scale, Low‑Latency Data Solutions with Bigtable Architect and optimize large‑scale NoSQL data stores using Google Cloud Bigtable to support real-time, high-throughput systems such as digital interactions, event processing, and operational intelligence. Cloud‑Native Pipelines & Event Architecture Build modern data ingestion and processing frameworks using Dataflow, Pub/Sub, and GKE, reflecting cloud‑native competencies described in enterprise architect roles. API‑Enabled Data Services Design secure, performant, reusable data APIs leveraging Apigee and enterprise integration patterns to enable data‑as‑a‑service across the organization. Platform Governance, Security & Resiliency Champion secure‑by‑design patterns, observability, non‑functional requirements, and data governance practices consistent with Huntington’s architecture standards. Cross‑Functional Collaboration & Influence Partner with engineering, analytics, and business groups to ensure data capabilities align with enterprise strategy, mirroring collaborative expectations from senior architect roles.

Requirements

Bachelor’s degree (or equivalent practical experience) in Computer Science, Information Systems, Engineering, or a related field
Minimum 7 years of experience in data architecture, solution architecture, or cloud‑based data engineering roles
Hands-on experience designing and delivering enterprise‑scale data architectures in cloud environments, with strong preference for Google Cloud Platform (GCP)
Proven ability to translate business requirements into target‑state data and solution architectures
Strong experience with cloud-native, event-driven, and streaming architectures
Experience designing scalable data ingestion, processing, and integration frameworks
Experience participating in architecture governance processes such as design reviews, standards definition, and architectural documentation

Nice To Haves

10+ years of experience in data architecture, solution architecture, or cloud‑based data engineering roles
Master’s degree in Computer Science, Information Systems, or a related discipline
Solid understanding of non-functional requirements including security, resiliency, performance, availability, and observability
Deep expertise with Google Cloud Platform services, includin Strong communication and collaboration skills, with the ability to influence engineering teams and partner with business and product stakeholders g Bigtable, Pub/Sub, Dataflow, Cloud Composer, GKE, and Apigee
Experience architecting high‑throughput, low‑latency operational data platforms using NoSQL or wide‑column databases (e.g. Bigtable or similar technologies)
Strong background in data governance, data quality, lineage, and metadata management
Experience implementing observability, monitoring, and resiliency patterns in cloud‑native data systems
Familiarity with DevSecOps practices, CI/CD pipelines, and infrastructure‑as‑code approaches
Experience working in large‑scale or regulated enterprise environments
Demonstrated ability to mentor engineers or architects and provide technical leadership across multiple teams
Google Cloud certifications such as Professional Cloud Architect or Professional Data Engineer (preferred but not required)

Responsibilities

Architect modern, cloud‑native data solutions using GCP’s advanced analytics and data engineering services.
Design resilient pipelines and ingestion frameworks that support batch, streaming, and real‑time workloads.
Apply best‑practice data modeling across conceptual, logical, and physical layers to support both operational and analytical use cases.
Lead solution design for Bigtable‑based, high‑velocity operational data platforms.
Collaborate with cross‑functional teams to define standards, patterns, and reusable frameworks that accelerate delivery.
Champion secure‑by‑design practices, performance optimization, observability, and governance across all data solutions.
Influence enterprise data strategy and help guide the evolution of our cloud data ecosystem.
Design conceptual, logical, and physical data models supporting analytical and operational use cases, aligned with Huntington’s enterprise data architecture patterns.
Architect and optimize large‑scale NoSQL data stores using Google Cloud Bigtable to support real-time, high-throughput systems such as digital interactions, event processing, and operational intelligence.
Build modern data ingestion and processing frameworks using Dataflow, Pub/Sub, and GKE, reflecting cloud‑native competencies described in enterprise architect roles.
Design secure, performant, reusable data APIs leveraging Apigee and enterprise integration patterns to enable data‑as‑a‑service across the organization.
Champion secure‑by‑design patterns, observability, non‑functional requirements, and data governance practices consistent with Huntington’s architecture standards.
Partner with engineering, analytics, and business groups to ensure data capabilities align with enterprise strategy, mirroring collaborative expectations from senior architect roles.