Senior Staff Data Engineer — Remote — Cloud Leader

Capital One; Little Rock (AR); A distancia; USD 286.000 - 327.000; Jornada completa

Descripción de la vacante

Capital One is hiring a Senior Staff Data Engineer (Remote-Eligible) to help shape future data platforms and banking in the cloud. You will lead and contribute technically across data pipelines, sharing capabilities, and governance, mentoring engineers, and driving innovation at scale.

The role requires deep AWS, lakehouse, Kafka, Flink, Spark, Snowflake, and Databricks expertise, with a focus on end‑to‑end data solutions and collaboration across business lines.

Formación

• Bachelor’s Degree in Computer Science or 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
• At least 4 years designing end-to-end data solutions in relational and non-relational databases

Responsabilidades

• Lead technical strategy for data pipelines and sharing capabilities
• Mentor engineers and recruit to grow Capital One Tech
• Drive engineering excellence and reusable solutions
• Communicate with stakeholders across the organization
• Own end-to-end design and coding of critical data projects
• Develop roadmaps integrating innovations into the data platform
• Ensure unified, scalable, governed data flow across the enterprise

Conocimientos

Python

Java

Scala

Educación

Bachelor’s degree in Computer Science or related field

Master’s degree (preferred)

Herramientas

AWS

Kafka

Flink

Spark

Snowflake

Databricks

Airflow

EMR

Descripción del empleo

Capital One is hiring a Senior Staff Data Engineer (Remote-Eligible) to help shape future data platforms and banking in the cloud. You will lead and contribute technically across data pipelines, sharing capabilities, and governance, mentoring engineers, and driving innovation at scale.

The role requires deep AWS, lakehouse, Kafka, Flink, Spark, Snowflake, and Databricks expertise, with a focus on end‑to‑end data solutions and collaboration across business lines.