Remote Senior Data Engineer - Lead Data Platform & Pipelines

Capital One; Indianapolis (IN); Remote; USD 286,000 - 327,000; Full time

Job summary

Capital One is seeking a Sr. Staff Data Engineer (Remote-Eligible) to join the Pipelines and External Data team.

You will lead technical strategy for data pipelines, data sharing, and platform scalability across business units, mentoring engineers and driving architectural standards. You will own end-to-end data projects, influence data governance, and push for innovative solutions in AWS, Lakehouse, and real-time data processing.

Qualifications

• Bachelor’s degree in CS or a related quantitative field.
• At least 9 years of experience in data engineering.
• At least 5 years in data architecture.
• At least 3 years building applications in AWS.
• At least 7 years programming in Python, Java or Scala.
• At least 6 years designing and developing data pipelines.

Responsibilities

• Build awareness and drive adoption of modern data tech across Capital One.
• Balance lending expertise with inclusive collaboration across teams.
• Promote engineering excellence and re-use of solutions.
• Communicate effectively with stakeholders at all levels.
• Be a trusted advisor for specific data platforms and capabilities.
• Mentor internal talent and assist in recruitment.
• Drive strategic direction for data engineering and emerging trends.
• Lead alignment across data systems and unify data architecture.

Skills

Data engineering

Data architecture

AWS

Python

SQL

Scala

Java

Data pipelines

Data modeling

Mentoring

Education

Bachelor’s Degree in CS or related quantitative field

Master’s Degree (preferred)

Tools

EMR

Spark

Glue

Databricks

Snowflake

Redshift

Job description

Capital One is seeking a Sr. Staff Data Engineer (Remote-Eligible) to join the Pipelines and External Data team.

You will lead technical strategy for data pipelines, data sharing, and platform scalability across business units, mentoring engineers and driving architectural standards. You will own end-to-end data projects, influence data governance, and push for innovative solutions in AWS, Lakehouse, and real-time data processing.