Senior Data Engineer: Cloud Data Pipelines & ML Solutions

Capital One Group; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking experienced Data Engineers to design, build, and scale cloud-first data solutions across the data platform. You will collaborate with Agile teams to deliver end-to-end data pipelines, mentor teammates, and drive data-driven decision making for millions of customers.

The role emphasizes Python, SQL, Spark, Databricks and Snowflake, with a strong focus on security, scalability, and operational excellence in a fast-paced environment.

Qualifications

• Bachelor's degree or higher in CS or related quantitative field (Statistics, Economics, OR, Analytics, Mathematics, Engineering)
• At least 4 years of experience in application development
• At least 2 years of experience in distributed data
• At least 2 years of experience with SQL
• At least 2 years of experience in data pipeline design and development
• At least 1 year of experience in data modeling and end-to-end data solutions using relational and non-relational databases

Responsibilities

• Design, develop, test, implement, and support data engineering solutions in a full-stack environment
• Collaborate with Agile teams and guide data analysts and scientists on data platforms
• Build scalable, cloud-first data pipelines with a focus on security and compliance
• Architect reusable data patterns and ensure code quality and maintainability
• Communicate data outcomes clearly to stakeholders to drive alignment

Skills

Python

SQL

Spark

Distributed data

Education

Bachelor's degree or higher in Computer Science or related quantitative field

Tools

Databricks

Snowflake

EMR

NoSQL databases

Job description

Capital One is seeking experienced Data Engineers to design, build, and scale cloud-first data solutions across the data platform. You will collaborate with Agile teams to deliver end-to-end data pipelines, mentor teammates, and drive data-driven decision making for millions of customers.

The role emphasizes Python, SQL, Spark, Databricks and Snowflake, with a strong focus on security, scalability, and operational excellence in a fast-paced environment.