Senior Data Engineer, CloudOps & Resilient Pipelines

Capital One; Riverwoods (IL); On-site; USD 179,000 - 205,000; Full time

Job summary

Capital One is seeking a Data Engineer 4 in Riverwoods, IL to collaborate with Agile teams and deliver cloud-first data solutions using Python, Spark, and Databricks. You will design scalable data pipelines, ensure data security, and mentor peers while aligning with enterprise data strategies.

The role emphasizes resilience, performance, and collaboration with product managers, software engineers, and data scientists to empower millions of customers with reliable data experiences.

Qualifications

• Bachelor's degree required in Computer Science or a related quantitative field.
• Minimum 4 years in application development.
• Minimum 2 years in distributed data environments.
• Minimum 2 years of SQL experience.
• Minimum 2 years in at least one programming language (Python, Java, or Scala).
• 2+ years in data pipeline design and development.
• 1+ year in end-to-end data solutions using relational and non-relational databases.

Responsibilities

• Collaborate with Agile teams to design, develop, test, and support data solutions.
• Influence teams with expertise in lakehouse architecture and full-stack systems.
• Build cloud-first data solutions with Python/Spark and Databricks/Snowflake.
• Mentor data community members and share technical knowledge.
• Design scalable, secure, and maintainable data pipelines and platforms.

Education

Bachelor's degree in Computer Science or related quantitative field

Tools

Python

Spark

SQL

Java

Scala

Databricks

Snowflake

Redshift

EMR

Glue

Airflow

Dagster

MongoDB

Cassandra

DynamoDB

Job description

Capital One is seeking a Data Engineer 4 in Riverwoods, IL to collaborate with Agile teams and deliver cloud-first data solutions using Python, Spark, and Databricks. You will design scalable data pipelines, ensure data security, and mentor peers while aligning with enterprise data strategies.

The role emphasizes resilience, performance, and collaboration with product managers, software engineers, and data scientists to empower millions of customers with reliable data experiences.