Distinguished Data Engineer - Capital One

OpenTalent; McLean (VA); On-site; USD 150,000 - 230,000; Full time

Job summary

Capital One is seeking a Distinguished Data Engineer to lead scalable data architectures integrating Databricks and Snowflake while ensuring cost-effectiveness and resilience. The role requires strong AI/ML knowledge and technical leadership to align platform developments with business goals.

As an individual contributor, you will mentor teams, evangelize best practices in the data engineering domain, and help grow Capital One’s technology capabilities across the Global Payment Network (GPN)

Qualifications

• Bachelor’s Degree
• At least 7 years of experience in data engineering
• At least 3 years of experience in data architecture
• At least 2 years of experience building applications in AWS

Responsibilities

• Lead the design and implementation of scalable data architectures integrating Databricks and Snowflake
• Drive performance engineering for large-scale data ingestion and processing workloads (Databricks, Snowflake, AWS)
• Provide technical leadership for AI/ML-enabled data solutions and workflows
• Champion engineering best practices and knowledge sharing across Capital One teams
• Mentor internal talent and recruit on the broader Capital One engineering community

Job description

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.

About the team

The Global Payment Network (GPN) Technology organization designs, builds, and operates the mission-critical systems and infrastructure that seamlessly power complex money movement across domestic and international rails. We build and operate a high-volume, low-latency, and highly resilient distributed ecosystem that is simultaneously secure, performant, accurate, and nimble.

Responsibilities

Lead the design and implementation of highly scalable, fault-tolerant, and cost-effective data architectures that seamlessly integrate Databricks (for complex processing,ML) and Snowflake (for warehousing,ETL).

Drive performance engineering and optimization for large-scale data ingestion and processing workloads across the Databricks,Snowflake,AWS data pipeline.

Provide technical leadership for the design, development, testing and deployment of agentic workflows across Capital One.This position requires a combination of strategic thinking, technical expertise in AI,ML and strong leadership to align the platform with business goals

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

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

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

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

Basic Qualifications:

Bachelor’s Degree

At least 7 years of experience in data engineering

At least 3 years of experience in data architecture

At least 2 years of experience building applications in AWS