This role pays more than
97%
of similar roles. Most pay
$140,262–$233,112
— the shaded band above.
At the midpoint, this role pays about
$337k
versus about
$187k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
1435 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 702 roles with salary data.
Senior Director, Data Engineer leads high-performing engineering teams within the Identity Analytics & Intelligence organization to define the future of data platforms and banking in the cloud. This role involves managing a large organization across data engineering, machine learning, and security products while owning multi-year roadmaps for identity analytics and AI/ML security platforms. The position requires building low-latency, event-driven systems for real-time decisioning using streaming telemetry, behavioral signals, and context graphs. Key responsibilities include developing robust ML infrastructure, advancing MLOps practices, and implementing LLM and GenAI techniques for threat intelligence. Candidates must possess expertise in Python, Java, or Scala, along with experience in SQL, Spark, and various cloud environments. The role addresses the critical challenge of securing workloads, non-human identities, and AI agents while ensuring compliance with audit and regulatory requirements through automated governance functions.
Define and own the multi-year roadmap for identity analytics, access decisioning, and AI/ML security platforms.
Lead and grow a 50+ person organization across Data Engineering, ML, Generative AI, and Security Products.
Review technical architectures, model designs, and system trade-offs to ensure high performance and reliability.
Architect low-latency, event-driven systems for real-time identity decisioning based on streaming telemetry and graph data.
Build and maintain robust ML infrastructure and pipelines for feature extraction, training, evaluation, and deployment.
Drive MLOps evolution through automated, metrics-backed deployment workflows and scalable monitoring for production models.
Implement LLM and GenAI techniques for threat intelligence, incident triage, and adaptive access-policy recommendations.
Operate an automated governance function to ensure compliance with NIST controls and audit requirements.
What we're looking for
Bachelor’s Degree in Computer Science or a related quantitative field.
At least 9 years of experience in data engineering.
At least 7 years of people management experience.
At least 7 years of programming experience with Python, Java, or Scala.
At least 5 years of experience driving technical delivery of roadmap features.
At least 6 years of experience designing and developing data pipelines.
At least 4 years of experience in data modeling and designing end-to-end solutions using relational and non-relational databases.
Master’s Degree in Computer Science or a related field (preferred); 12+ years of application development; 8+ years of cloud, distributed systems, streaming pipelines, and warehouse experience (preferred).
Azure
Python
SQL
Spark
Databricks
Azure Data Factory
Data Lake
Synapse Analytics
Azure Functions
ETL
Hadoop
NoSQL
Big Data
Data Modeling
Data Warehousing
DevOps
Real-Time Processing