Senior Data Engineer: Cloud Pipelines & Data Platforms

capitalone; Richmond (VA); On-site; USD 179,000 - 205,000; Full time

Benefits offered by this job

Health benefits

Inclusive culture

Job summary

Capital One is seeking a Data Engineer 4 (Manager, IC) in Richmond, VA to design and deliver cloud-first data solutions in a fast-paced, collaborative environment. You will mentor teams and drive data platforms using Python, Spark, Databricks, and Snowflake to empower millions of Americans.

The role requires 4+ years in application development, 2+ years in distributed data and SQL, plus cloud experience across AWS/Azure/GCP.

Qualifications

• Bachelor’s Degree in Computer Science or related field.
• 4+ years in application development and 2+ years in distributed data.
• 2+ years with SQL and at least 2 years in one programming language (Python/Java/Scala).
• 2+ years in data pipeline design and development.
• 1+ year in data modeling using relational and non-relational databases.

Responsibilities

• Collaborate with Agile teams to design, develop, test, and support solutions.
• Influence a team of developers, analysts, and data scientists.
• Create cloud-first data solutions with emphasis on scalability and security.
• Architect common data engineering patterns for quality and reusability.
• Communicate data outcomes to stakeholders to drive alignment.

Skills

Python

SQL

Spark

Distributed data

Cloud experience

Mentoring

Data modeling

Data pipelines

Databricks

Snowflake

Education

Bachelor's Degree in Computer Science or related field

Tools

Databricks

Snowflake

EMR

Spark

Glue

Job description

Capital One is seeking a Data Engineer 4 (Manager, IC) in Richmond, VA to design and deliver cloud-first data solutions in a fast-paced, collaborative environment. You will mentor teams and drive data platforms using Python, Spark, Databricks, and Snowflake to empower millions of Americans.

The role requires 4+ years in application development, 2+ years in distributed data and SQL, plus cloud experience across AWS/Azure/GCP.