Senior Data Engineer - Pipelines & Lakehouse Platforms

Capital One; Oklahoma City (OK); On-site; USD 140,000 - 210,000; Full time

Job summary

Capital One is seeking a Sr. Staff Data Engineer to lead the technical strategy for data pipelines and data sharing across the enterprise.

This individual contributor role demands hands-on coding (Python/SQL/Java/Scala) and visionary leadership across teams to drive platform scalability and operational excellence. You will mentor engineers, promote best practices, and influence stakeholders while delivering next-generation data solutions on AWS, Kafka, Flink, Spark, Snowflake, and Databricks.

Qualifications

• Bachelor’s Degree required; 9+ years in data engineering; 5+ years in data architecture; 3+ years building AWS applications
• Masters’ Degree preferred; 10+ years experience in data engineering; data modeling experience; ontology standards exposure
• Proficiency with Python/SQL/Scala/Java; strong analytical and problem-solving skills

Responsibilities

• Build awareness and drive adoption of modern data technologies across teams
• Balance deep technical work with inclusive leadership and mentorship
• Promote engineering excellence and encourage reusability of solutions
• Communicate with stakeholders across the enterprise to influence decisions
• Act as trusted advisor for technology domains and platform capabilities
• Mentor and help recruit talent to strengthen Capital One’s tech capability

Skills

AWS

Data engineering

Data architecture

Python/Java/Scala

Mentoring

Education

Bachelor’s Degree

Master’s Degree

Tools

Kafka

Flink

Spark

Snowflake

Databricks

Python

SQL

Java

Scala

Job description

Capital One is seeking a Sr. Staff Data Engineer to lead the technical strategy for data pipelines and data sharing across the enterprise.

This individual contributor role demands hands-on coding (Python/SQL/Java/Scala) and visionary leadership across teams to drive platform scalability and operational excellence. You will mentor engineers, promote best practices, and influence stakeholders while delivering next-generation data solutions on AWS, Kafka, Flink, Spark, Snowflake, and Databricks.