GCP Data AI Architect

Job Description

Job Title: Lead GCP Data AI Architect

\n

Location: Charlotte, NC (Hybrid)

\n

Contract

\n

\n

JD:

\n

Role Overview

\n

We are seeking a highly experienced Lead Data & AI Architect & Strategy consultant with deep expertise in Google Cloud Platform (GCP) to lead the architecture for a strategic Data and AI transformation program within a leading financial-services organization. This is a critical technology leadership role with end-to-end responsibility for defining and governing the Data and AI architecture across the transformation lifecycle, from current-state discovery and assessment through target-state architecture, implementation planning and implementation. The role will establish the architectural direction, drive key technology decisions and provide technical leadership to ensure the platform is scalable, secure, resilient and capable of supporting enterprise-grade Data, AI and agentic AI use cases.

\n

\n

Key Responsibilities

\n

Data & GCP Architecture

\n

Design and govern enterprise-scale data platforms on GCP supporting batch, real-time and streaming workloads.

\n

Architect data ingestion, processing, storage, transformation, serving and consumption patterns using GCP-native services.

\n

Provide deep architectural guidance across BigQuery, Cloud Storage, Dataplex, Dataflow/Apache Beam, Pub/Sub, Dataproc, Vertex AI and related GCP services.

\n

Define modern data architecture patterns, including lakehouse/Medallion architecture, enterprise data models and data products where appropriate.

\n

Design high-volume data workloads with appropriate approaches to performance, scalability, resilience, availability and cost optimization.

\n

Define enterprise integration patterns across applications, APIs, databases and other data sources.

\n

Establish BigQuery architecture and optimization strategies, including data modeling, partitioning, clustering and workload management.

\n

\n

\n

Required Skills & Experience

\n

12+ years of experience in Data, AI, Cloud or Enterprise Architecture, with significant experience leading large-scale technology transformation programs.

\n

Extensive experience designing and implementing enterprise-scale solutions on GCP.

\n

Deep expertise in GCP data and AI services, including BigQuery, Cloud Storage, Dataflow/Apache Beam, Pub/Sub, Dataproc and Vertex AI.

\n

Strong experience designing modern enterprise data platforms and architectures, including data lakes/lakehouses, data warehouses, data products and streaming platforms.

\n

Proven experience designing both batch and real-time/streaming data architectures.

\n

Strong experience with AI/ML architecture and practical experience with Generative AI and/or agentic AI architectures.

\n

Strong understanding of RAG, vector search, embeddings, knowledge architectures, AI orchestration and integration of AI agents with enterprise systems and data.

\n

Experience designing secure, governed and production-grade AI platforms.

\n

Strong understanding of data security, governance, privacy, lineage and data quality.

\n

Proven experience working within financial services, banking or other highly regulated industries.

\n

Experience leading architecture discovery, assessment and transformation engagements.

\n

Demonstrated ability to translate business requirements and current-state findings into target-state architecture and implementation roadmaps.

\n

Strong understanding of cloud scalability, resilience, performance, observability and cost optimization.

\n

Experience with DevOps/MLOps and productionization of Data and AI solutions.

\n

Excellent executive communication, stakeholder management and influencing skills.

\n

Proven ability to lead and mentor multidisciplinary architecture and engineering teams.

\n

\n

Preferred Qualifications

\n

Google Cloud Professional Cloud Architect and/or Professional Data Engineer certification.

\n

Experience with production-scale agentic AI platforms and enterprise AI implementations.

\n

Experience with Vertex AI and Google Cloud generative AI capabilities.

\n

Experience with enterprise data governance, metadata, catalog and lineage platforms.

\n

Experience with Infrastructure as Code, CI/CD and modern cloud engineering practices.

\n

Experience defining enterprise architecture standards and technology reference architectures.

\n

Experience working directly with C-suite and senior technology leadership in complex transformation programs.