Distinguished Data Engineer - Enterprise Data Technology

Distinguished Data Engineer - Enterprise Data Technology

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 Data Operations Center (DOC) serves as the backbone of our enterprise data ecosystem, ensuring the stability and scalability of our core e-data platforms. As a horizontal organization, we manage a diverse tech stack including Snowflake, Databricks, Dynamo

DB, File Transfers and legacy systems like Ab Initio to provide a high-performance foundation for the entire enterprise while housing an internal AI,ML Engineering team focused specifically on our evolution. By integrating AI,ML directly into our operations, we are transforming our model from reactive maintenance to a predictive, self-healing, and automated platform architecture. This collaborative structure ensures that the organization continuously evolves its support mechanisms, moving from reactive to predictive and automated operations.

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 inner source 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

• At least 5 years of experience of Python, SQL or Scala

• At least 3 years of experience developing AI and ML algorithms or technologies

Preferred Qualifications:

• Masters’ Degree

• 5+ years of experience in data engineering (Hadoop,AWS,Snowflake,ETL etc.)

• 5+ years of experience in Data Governance, Data Governance Platforms, Data Standardization, and Data Modeling

• 5+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

• Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and Vector
  
  DBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

• Deep proficiency and strategic experience with Databricks (e.g., Delta Lake, Unity Catalog, MLflow, performance tuning Spark workloads).

• Deep proficiency and…