Enterprise Data Architect (Enterprise Data & Cloud Modernization)

Role Overview

This is not a traditional data architect role. We are seeking an Enterprise Data Architect to help reshape how a large organization designs, governs, and scales its data ecosystem. You will lead the modernization of legacy Teradata platforms into a cloud-first BigQuery architecture, define enterprise data domain and Data-as-a-Product strategies, and serve as the bridge between executive vision and technical execution. This is a strategic, high-impact position influencing the future of enterprise analytics.

What You’ll Do

· Executive & Strategic Leadership

· Lead executive-level discussions with SVPs and senior leadership to assess current enterprise data capabilities and define future-state architecture

· Conduct enterprise data platform maturity assessments across architecture, integration, governance, and domain ownership

· Facilitate architecture workshops with technical leaders, platform SMEs, and executive stakeholders

· Serve as the bridge between enterprise vision and hands-on engineering execution

Enterprise Data Ecosystem Design

· Design and articulate enterprise-scale data ecosystems, including patterns and approaches for:

· Data curation frameworks, including medallion architecture (raw / curated / consumption layers)

· Data-as-a-product operating models, including domain ownership and enablement strategies

· Data Mesh patterns and federated governance approaches

· Customer data management, including unified customer modeling

· Financial KYC modeling experience is a strong plus

· Open Semantic frameworks (OSI) and semantic layer strategy

· Enterprise data domain architecture and integration contracts

· Canonical modeling and domain-driven design principles

Cloud & Modernization Architecture

· Evaluate existing Teradata data warehouse environments and design migration / modernization approaches into Google Cloud

· Architect scalable data platforms centered on BigQuery and Google Cloud Storage

· Define best practices for cloud storage, lifecycle management, and access patterns

· Design event-driven architectures using Pub/Sub

· Architect large-scale processing solutions using Dataflow and Dataproc (Spark)

· Establish IAM, security boundaries, and governance frameworks within Google Cloud Platform

· Define cost optimization strategies using partitioning, clustering, workload isolation, and query design

Prototyping & Hands-On Validation

· Build and validate prototype solutions in Google Cloud Platform / BigQuery to demonstrate architectural feasibility

· Partner with engineering teams to ensure architecture patterns are deployable and scalable

· Provide hands-on guidance in performance optimization and cost control

Governance & Enablement

· Design enterprise-scale data governance models

· Define data access controls, lifecycle policies, and compliance-aligned usage standards

· Establish architectural guardrails to prevent legacy anti-patterns in cloud implementations

· Support enablement strategies that empower domains while maintaining enterprise standards

What You Bring

· Proven experience as an Enterprise Data Architect in large, complex organizations

· Strong background in Teradata and modern cloud data platforms, specifically Google BigQuery

· Deep expertise in enterprise data domain design, modeling standards, and integration architecture

· Experience defining data ecosystem operating models (Data Mesh, Data-as-a-Product)

· Strong understanding of medallion architecture patterns

· Experience with unified customer data modeling; KYC domain knowledge preferred

Hands-on experience with:

· BigQuery

· Google Cloud Storage

· Pub/Sub

· Dataflow and/or Dataproc (Spark)

· IAM and enterprise cloud governance

· Looker / LookML

· Familiarity with Open Semantic frameworks (OSI)

· Advanced SQL and cloud cost optimization expertise

· Exceptional ability to communicate architecture strategy to both executive and technical audiences

Ideal Candidate Profile

You are as comfortable in a boardroom defining enterprise data strategy as you are whiteboarding medallion architecture patterns or prototyping a BigQuery data product.

You understand both legacy data warehouse ecosystems and modern cloud-native data architectures — and you know how to guide organizations through the transformation from one to the other without compromising governance, scalability, or long-term sustainability.

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