Senior Data Engineer: Cloud Pipelines & ML Enablement

Capital One Group; Northern, New York (KY, NY); Hybrid; USD 197,000 - 225,000; Full time

Job summary

Capital One is seeking a Data Engineer 4 for Nexus Products to design, build, and optimize data pipelines in a cloud-first environment. You will work with Agile teams to deliver robust data solutions leveraging Python, SQL, Spark, and modern data warehouses.

The role emphasizes scalable, secure, and compliant data architectures, mentoring colleagues, and collaborating with data analysts and scientists to empower financial services for millions of customers.

Qualifications

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

Responsibilities

• Collaborate with Agile teams to design, develop, test, and support data solutions.
• Design and deliver cloud-first data pipelines and platforms with scalability and resilience.
• Mentor other data community members and communicate data outcomes to stakeholders.
• Architect and enforce common data engineering patterns for code quality and reuse.
• Implement data security standards and ensure compliance with privacy regulations.

Skills

Python

SQL

Java

Scala

Distributed data

Data pipelines

Data modeling

Data warehousing

Education

Bachelor's degree in Computer Science or related field

Tools

AWS

Azure

Google Cloud

Spark

Databricks

Snowflake

Redshift

Airflow

MongoDB

Job description

Capital One is seeking a Data Engineer 4 for Nexus Products to design, build, and optimize data pipelines in a cloud-first environment. You will work with Agile teams to deliver robust data solutions leveraging Python, SQL, Spark, and modern data warehouses.

The role emphasizes scalable, secure, and compliant data architectures, mentoring colleagues, and collaborating with data analysts and scientists to empower financial services for millions of customers.