Building & Launching Dataplex
In 2020, I began working directly with Snapchat—one of Google Cloud’s largest strategic customers, with a commitment exceeding $2 billion — at a time when their dissatisfaction with the platform was growing. Their challenges were massive and unmistakably clear: millions of data assets, complex access patterns, inconsistent metadata, and no reliable way to discover, classify, or govern data across their sprawling ecosystem. The existing Catalog API simply could not operate at Snapchat’s hyperscale. What began as routine troubleshooting quickly escalated into a critical signal: if Google Cloud could not support customers at this scale, the long-term trustworthiness and competitiveness of the platform was at risk. Throughout 2020, I worked directly with Snap’s senior engineering leaders and Google Cloud’s executive team to document pain points, align on requirements, and understand the deeper architectural deficiencies that enterprises were starting to face across the industry—not just Snap.
By early 2021, we had enough alignment to take action. We initiated a joint Google–Snap prototyping effort to explore what a modern, domain-oriented governance layer could look like. I led the conceptual shaping of the prototype—defining a functional architecture that could unify metadata across projects, organize datasets into business domains, centralize governance, and provide scalable access control. I worked closely with engineering, PMs, architects, and VPs to make sure the prototype directly reflected customer realities, not theoretical best practices. Phase One was built rapidly, and when we delivered it to Snap, the outcome was undeniable: for the first time, they could see and govern their entire data estate coherently.
This early success triggered a critical inflection point. Google executives green-lit a full product investment, hiring a dedicated team of PMs, engineers, UX designers, and program managers to evolve the prototype into a globally scalable product. Throughout 2021, I partnered with this newly formed team as we ran weekly development sprints, incorporated customer feedback, and held quarterly executive stand-ups with leadership from both companies. I simultaneously led the private preview program, enrolling more than 700 customers across industries—banks, media companies, multinationals, retailers, telecom, and government agencies. This broadened validation effort transformed the prototype into a robust governance fabric capable of supporting enterprise-level requirements for metadata intelligence, data quality, access governance, and policy observability.
By 2022, the vision had matured—and Dataplex officially launched as one of Google Cloud’s most comprehensive data governance products. Adoption exceeded every projection: more than 1,400 customers onboarded within the launch window. Snapchat, whose escalation originally sparked the project, became a satisfied and vocal advocate. The same platform that began as an urgent customer-driven fix had evolved into a foundational architecture for distributed data governance across the global enterprise landscape.
Dataplex emerged at precisely the moment when governing data—not just storing it—became civilization-critical. Enterprises across the U.S., Europe, and Asia were facing the rise of GDPR enforcement, new U.S. privacy laws, Asia’s data sovereignty measures, and early AI governance frameworks requiring lineage, auditability, and continuous controls. As organizations accelerated cloud adoption and AI integration, they needed a governance model that was centralized in oversight yet decentralized in execution.
See this article for the original announcement from our Director and Group product Manager.
My contributions focused on five key areas:
Through my role, leading customer engagement, prototype development, partner deployment models, product launch and go-to-market execution… I helped shape Dataplex into the platform that now enables enterprises worldwide to govern data in the era of AI.
1. Managing the go-to-market launch end-to-end
I led the GTM launch process, ensuring engineering, product, marketing, analyst relations, and field teams were aligned on Dataplex’s value prop: creating a unified governance layer on top of distributed data. This required translating deeply technical features—metadata unification, domain-based policy management, serverless exploration, data quality pipelines—into narratives tailored for CIOs, CDOs, architects, and developers.
2. Defining a robust partner deployment model
I worked closely with Deloitte, Accenture, PwC, and Collibra to build a repeatable deployment approach. This aims to ensure Dataplex will be implemented at enterprise scale across diverse customer environments, where nuanced compliance and technical challenges may arise. This collaboration formed the backbone of Dataplex's early adoption and long-term ecosystem strategy.
3. Advancing Data Quality functionality with Product Management
I collaborated closely with PMs and engineers to shape Dataplex’s Data Quality capabilities—including rule-based checks, anomaly detection hooks, task orchestration, and BigQuery/GCS interoperability. This functionality is now the backbone of governance programs at multiple Fortune 500 companies.
4. Steering product leadership and executive stakeholders
I led alignment efforts across directors, VPs, and product area leaders to ensure Dataplex invested in the right capabilities at the right time—metadata intelligence, domain-level IAM, policy propagation, and federated analytics support. These decisions shaped Dataplex’s evolution into a truly enterprise-grade governance platform.
5. Working hands-on with flagship customers
From Snap to top global banks and international media platforms, I partnered with our most data-intensive customers to validate requirements, gather feedback, and ensure Dataplex delivered real impact. Snap’s early adoption—spanning petabytes of data and thousands of users—became one of the strongest signals of Dataplex’s value in the wild.
Dataplex now stands as an intelligent data fabric that brings order, governance, and trust to distributed data. It supports organizations moving from monolithic pipelines to business-domain ownership—while still maintaining centralized visibility and control.
I’m proud of the role I played in bringing this product to market, shaping its partner and customer strategy, and maturing its data intelligence capabilities. As enterprises continue to evolve toward data mesh and distributed governance models, Dataplex is becoming a foundational part of that journey—and helping customers trust their data at scale.
Lakes & Domains
Logical containers that represent business domains (Marketing, Supply Chain, Risk, etc.), allowing domain-level IAM and policy assignment.
Assets & Zones
Abstractions that allow organizations to classify and structure data—raw, refined, curated—while maintaining lineage and business context.
Metadata Intelligence
Dataplex automatically crawls, extracts, and updates metadata across BigQuery and GCS, exposing it for discovery and enrichment through the Data Catalog API surface.
Interoperability for Open Analytics
Dataplex automatically materializes external tables and publishes metadata to power open-source engines like Spark, Presto, and Hive—making governance compatible with multi-tool ecosystems.
Central Policy Management
Administrators can define governance, access, and compliance policies once and propagate them across distributed assets—mirroring how enterprises actually operate.
Built-in Data Quality
Rules, tasks, and serverless operational pipelines surface issues before they reach analytical or ML workloads.
Unified Observability
Connected to Cloud Logging and Monitoring, Dataplex offers audit trails, quality metrics, operational telemetry, and domain-level lineage signals
Why this matters for the future:
As geopolitical competition intensifies and nations race to define the rules of the AI era, the ability for enterprises to govern data at scale has become a strategic imperative—not just for compliance, but for national resilience and global interoperability. Dataplex sits at the center of this shift: a unifying data fabric capable of organizing, securing, and monitoring distributed data across borders, business domains, and cloud environments. In a world where E.U. GDPR, U.S. privacy laws, and emerging Asian data-sovereignty frameworks increasingly shape digital policy, Dataplex provides the technical foundation that allows organizations to operate more confidently within a fragmented regulatory landscape.
By helping lead Dataplex’s go-to-market strategy, partner ecosystem, and customer adoption, I contributed to building the governance layer that will underpin the next few decades of AI-driven decision systems. And as AI models scale, fuse with global supply chains, and influence financial markets, military planning, healthcare, and democratic institutions, the trustworthiness of underlying data becomes a geopolitical lever in itself. Dataplex is more than a product—it is an architectural shift, enabling enterprises and governments alike to harness AI’s power in the cloud, without sacrificing compliance, sovereignty, or the stability of the broader digital ecosystem..
