Principal Data Architect

PayPal•San Jose, CA

3d•Hybrid

About The Position

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers. We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards. Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. Our beliefs are the foundation for how we conduct business every day. We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities. Job Summary: PayPal is seeking a Principal Data Engineer with 15+ years of experience to lead the design and evolution of enterprise-wide data architecture. This role sits at the intersection of data engineering, analytics, instrumentation, and governance — driving how PayPal captures, structures, and democratizes data across its global payments platform. You will own the end-to-end data strategy for instrumentation pipelines, define and steward the enterprise Data Dictionary, and partner with analytics, product, and engineering teams to ensure data is accurate, discoverable, and trustworthy at scale. Job Summary We are seeking a Principal Data Architect to lead the data strategy, instrumentation standards, and data quality transformation for the Checkout organization. This is one of the most strategically critical individual contributor roles in Checkout Engineering — a high-visibility position that demands both deep technical authority and the executive influence to shape how hundreds of engineers and product managers think about and work with data. The ideal candidate has an established track record of driving large-scale data transformations as an individual contributor in complex, matrixed organizations. You don't manage through headcount — you lead through technical credibility, organizational influence, and the ability to build durable systems and standards that outlast any single initiative. Your Way to Impact You will establish the data architecture foundation that enables the Branded Checkout organization to move from reactive data consumption to proactive, insight-driven product development. By creating a Center of Excellence for data instrumentation, a canonical Data Dictionary, and AI-powered governance tooling, you will directly accelerate PayPal's ability to experiment faster, make better product decisions, and democratize data access across one of the company's most critical engineering organizations.

Requirements

10+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
Minimum of 15 years of relevant experience in data architecture, data engineering, or related disciplines, with a Bachelor's degree or equivalent; advanced degree preferred
Demonstrated Principal-level impact as an individual contributor — a track record of driving architecture decisions and data transformation programs across large, complex, matrixed organizations
Deep expertise in cloud data architecture, with hands-on GCP experience required (BigQuery, Dataflow/Apache Beam, Pub/Sub, Cloud Composer/Airflow, Vertex AI, GCS, Looker)
Proven experience designing and implementing data instrumentation frameworks, event schemas, and behavioral analytics pipelines at scale
Strong background in data governance, data quality frameworks, data lineage, and metadata management (e.g., Data Catalogs, Data Dictionaries, dbt)
Experience building or deploying AI/ML or agentic solutions to automate data quality, code review, or pipeline management workflows
Expertise in data modeling (dimensional, relational, and document models), stream and batch processing architectures, and distributed systems design
Demonstrated ability to influence executive and senior engineering leadership without direct reporting authority
Exceptional written and verbal communication skills; able to translate complex data architecture concepts for both technical and non-technical audiences

Nice To Haves

Experience in payments, fintech, or high-volume e-commerce platforms with complex transactional data environments
Familiarity with data mesh principles and experience implementing domain-oriented data ownership models
Experience with experimentation platforms and A/B testing infrastructure; understanding of how instrumentation quality directly impacts experiment validity
Knowledge of data privacy, compliance, and regulatory requirements (PCI-DSS, GDPR, CCPA) as they apply to data architecture in payments contexts
Familiarity with additional cloud platforms (AWS, Azure) and hybrid/multi-cloud data architectures
GCP Professional Data Engineer or GCP Professional Cloud Architect certification
Sets data architecture direction for a critical business domain and creates clarity amidst ambiguity
Influences across organizational boundaries with strong technical judgment and pragmatic decision-making
Builds durable standards and guardrails that improve quality and velocity simultaneously
Models operational excellence and raises the engineering bar through technical mentorship and leverage
Operates across Engineering, Product, Data Science, and Analytics — translating technical possibilities into business outcomes

Responsibilities

Develop and implement the overall data engineering strategy, aligning with corporate goals and objectives.
Lead the design and execution of advanced data engineering projects to support strategic decision-making.
Collaborate with executive leadership to identify and prioritize data-driven opportunities.
Oversee the development and maintenance of data infrastructure, ensuring scalability and efficiency.
Ensure compliance with data privacy and security regulations.
Drive innovation in data engineering practices and tools, staying ahead of industry trends.
Establish a Center of Excellence for Instrumentation Define and operationalize instrumentation guidelines for the Branded Checkout organization.
Set the standard for how events, signals, and behavioral data are captured across web, mobile, and backend surfaces.
Create a governance model that scales across squads without creating bottlenecks.
Own and Drive the Branded Checkout Data Dictionary Design, build, and maintain the authoritative Data Dictionary for the XO organization — a single source of truth for data definitions, ownership, lineage, and quality standards.
Ensure the Dictionary is living, versioned, and integrated into engineering workflows.
Drive Engineering and Product Adoption of Data Standards Partner with engineering leadership, product management, and data consumers to drive broad adoption of instrumentation best practices and the Data Dictionary.
Influence without authority at scale — across dozens of squads and multiple product verticals within Checkout.
Partner with Data & Analytics to Develop Instrumentation Standards Work closely with the Data and Analytics organization to co-develop organization-wide instrumentation standards.
Collaborate with peer architects to incorporate these standards into shared frameworks and platform tooling, making compliance the path of least resistance.
Co-Architect Agentic Solutions for Instrumentation Remediation Partner with other architects to design and deploy agentic AI solutions that systematically identify, prioritize, and remediate existing instrumentation that falls outside established standards — bringing the historical codebase into compliance at machine speed.
Develop AI-Powered PR Review Agents for Instrumentation Governance Design and implement AI agents that automatically review pull requests for instrumentation completeness, correctness, and adherence to standards.
Establish an automated gatekeeping mechanism that embeds data quality into the software delivery lifecycle.
Build a Self-Sustaining Data Culture in Engineering and Product Design enablement frameworks, reference architectures, and self-service tooling that empower engineering and product teams to leverage data and run experiments independently — reducing dependency on the Data & Analytics team and accelerating the pace of learning across XO.
Democratize Data Adoption Across Branded Checkout Partner with the Data & Analytics organization to identify and remove barriers to data access, literacy, and utilization across Branded Checkout.
Champion data-driven decision-making as a cultural norm, not just a technical capability.
Cloud Data Architecture — GCP as Primary Platform Design and implement scalable, cost-effective cloud-native data architectures on GCP (BigQuery, Dataflow, Pub/Sub, Vertex AI, Cloud Composer, and related services).
Establish best practices for data lake / data warehouse design, streaming pipelines, and data mesh patterns in a cloud-first environment.
Technical Leadership and Cross-Organizational Influence Represent the Checkout data architecture perspective in company-wide technical forums.
Mentor senior and staff engineers.
Present architecture strategies, trade-offs, and investment proposals to senior engineering and product leadership.
Set architecture direction, create clarity in ambiguity, and raise the engineering bar across the organization.

Benefits

At PayPal, we’re committed to building an equitable and inclusive global economy. And we can’t do this without our most important asset-you. That’s why we offer comprehensive, choice-based programs, to support all aspects of personal wellbeing—physical, emotional, and financial—delivering meaningful value where it matters most. We strive to create a flexible, balanced work culture with a holistic approach to benefits, including generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.

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