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Distinguished Data Engineers are individual contributors who strive to be diverse in thought so we visualize the problem space. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. Distinguished Engineers will significantly impact our trajectory and devise clear roadmaps to deliver next generation technology solutions. Deep technical experts and thought leaders that help accelerate adoption of the very best engineering practices, while maintaining knowledge on industry innovations, trends and practices. Visionaries, collaborating on Capital One’s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates. Role models and mentors, helping to coach and strengthen the technical expertise and know-how of our engineering and product community. Evangelists, both internally and externally, helping to elevate the Distinguished Engineering community and establish themselves as a go-to resource on given technologies and technology-enabled capabilities.
Job Responsibility:
Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed
leverage expertise to grow skills in the broader Capital One team
Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization
Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner
Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent
Zero-Registration Observability: Implement an automated discovery framework for 100% systemic data flow visibility without manual registration
Deterministic Inference Engine: Engineer an SCA/AST-based inference engine to map data logic in imperative code for compliance-grade lineage
Data Passport Protocol: Define a cross-boundary protocol to embed immutable metadata for end-to-end traceability across external systems
Advanced Static Analysis: Develop language-agnostic parsers to interpret data flow intent from codebases without requiring execution
Autonomous Triage: Interface the DCG with AI agents via MCP to enable autonomous Root Cause Analysis and real-time failure remediation
Map Data Movement: Prototype infrastructure-level data interception using kernel-level tools to create a geographic map of enterprise data movement
Simplification & Governance: Consolidate fragmented metadata silos into a single queryable graph and automate capture to eliminate documentation overhead
Requirements:
Bachelor’s Degree
At least 9 years of experience in data engineering
At least 5 years of experience in data architecture
At least 3 years of experience building applications in AWS
Nice to have:
Masters’ Degree
10+ years of experience in data engineering
3+ years of data modeling experience
2+ years of experience with ontology standards for defining a domain
2+ years of experience using Python, SQL or Scala
1+ year of experience deploying machine learning models
3+ years of experience implementing big data processing solutions on AWS
What we offer:
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)