Senior Staff Full-stack Engineer, Global Payments Network

Capital One • McLean, VA

1d • $314,800 - $392,000

About The Position

Capital One is hiring a Senior Staff Full-stack Engineer as an individual contributor for its Global Payment Network (GPN), a ground-up effort to unify Discover Network, PULSE, and Diners Club International into one modern payment network. The engineer will architect and deliver the real-time and batch data infrastructure that other network teams depend on, including ingestion, streaming, the canonical data model, and the catalog and metadata layer. The role operates across Core Network, Fraud/AML, Analytics, and Canonical Modeling, and combines deep technical expertise with architectural vision and cross-functional partnership. It has no direct reports.

The position calls for expertise in distributed systems, real-time streaming architecture, data modeling at scale, and cloud infrastructure. The Senior Staff Engineer will establish platform architecture and standards, advise across data engineering, and help build a portable, understandable platform using well-established components. The role also involves partnering with engineering, data science, product, risk, and partner teams to support their roadmaps and raise technical standards across the organization.

The listed full-time annual salary range is $314,800–$359,300 in McLean, Virginia, and $343,400–$392,000 in New York, New York. The position is eligible for performance-based incentive compensation, potentially including cash bonuses and/or long-term incentives. Capital One provides a comprehensive benefits offering; eligibility varies by employment status and management level.

Requirements

• Bachelor’s degree or higher in Computer Science or a related quantitative field, such as Statistics, Economics, Operations Research, Analytics, Mathematics, or Engineering.
• At least 9 years of experience in software engineering and solution architecture.
• At least 9 years of experience in enterprise architecture and design patterns.
• At least 9 years of experience in cloud computing, such as AWS, Microsoft Azure, or Google Cloud.
• At least 9 years of experience in data architecture.
• Deep understanding of distributed systems, real-time streaming architecture, data modeling at scale, and cloud infrastructure.

Nice To Haves

• Master’s degree in Computer Science or Software Engineering.
• 12 or more years of experience in software engineering and solution architecture.
• 12 or more years of experience in enterprise architecture and design patterns.
• 12 or more years of experience with web technologies, including JavaScript, TypeScript, and SPA frameworks.
• 12 or more years of experience designing and building distributed HPC and ML systems.
• 12 or more years of experience in cloud computing, such as AWS, Microsoft Azure, or Google Cloud.
• 12 or more years of experience in data architecture.
• Experience designing event-driven, real-time streaming architectures at scale, such as Kafka, Flink, or equivalent.
• Experience with distributed storage, catalog, and metadata/lineage systems, such as Iceberg and data lakehouse architectures.
• Experience designing canonical or shared data models that unify disparate or legacy systems.
• Experience architecting high-availability, low-latency distributed systems in regulated, high-stakes domains such as payments, fraud, or financial transaction processing.

Responsibilities

• Architect real-time, event-driven data pipelines for authorization, transaction, settlement, and fraud-relevant events, meeting payment-network latency and exactly-once delivery requirements.
• Define a canonical data model that reconciles the legacy schemes’ merchant hierarchies, participant identities, and transaction semantics, translating legacy formats at the network edge rather than propagating them inward.
• Design and build the catalog and metadata layer, including schema registry, lineage, data contracts, and access policy, as a trusted source of truth for downstream teams.
• Set technical architecture and standards for streaming, storage, and low-latency serving at network scale.
• Promote data standardization internally and with partner teams building on the platform.
• Serve as a technical authority and advisor for data engineering, shaping a modern, portable platform that favors open, well-understood components.
• Partner with Fraud/AML, Analytics, and Canonical Modeling leadership so the architecture supports their roadmaps.
• Mentor engineers and raise the technical bar across the organization without owning a reporting chain.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior