Senior Data Engineer: Python, AWS & GenAI Cloud Pipelines

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

Benefits offered by this job

Health benefits

Performance-based incentives

Job summary

Capital One is seeking a Data Engineer 4 to drive a major transformation across our Enterprise Platforms Technology group. You will build scalable, cloud-first data solutions using Python, Spark, Databricks, and Snowflake, collaborating with Agile teams and data scientists.

You will mentor others, shape data engineering patterns for maintainability, and ensure security and compliance across data pipelines. This role requires 4+ years in data engineering and a strong foundation in distributed

Qualifications

• Bachelor's Degree or higher in Computer Science or a related quantitative field.
• 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 one programming language (Python, Java, or Scala).
• 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.

Responsibilities

• Collaborate with Agile teams to design, develop, test, implement, and support technical solutions.
• Influence a team of developers, data analysts and data scientists with ML, distributed microservices, lakehouse, and full-stack systems.
• Use Python and Spark with relational, NoSQL databases and cloud data warehousing (Databricks, Snowflake).
• Mentor other data community members and stay current with data trends and technologies.
• Design and deliver cloud-first data solutions for scalable capabilities and impact.

Skills

Python

Spark

Education

Bachelor's degree in CS or related field

Tools

Databricks

Snowflake

AWS

Job description

Capital One is seeking a Data Engineer 4 to drive a major transformation across our Enterprise Platforms Technology group. You will build scalable, cloud-first data solutions using Python, Spark, Databricks, and Snowflake, collaborating with Agile teams and data scientists.

You will mentor others, shape data engineering patterns for maintainability, and ensure security and compliance across data pipelines. This role requires 4+ years in data engineering and a strong foundation in distributed