Senior AI Data Engineer: Real-time Pipelines & LLMs

Capital One; Plano (TX); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One seeks a senior Data Engineer to design and implement an AI-enabled data ecosystem that powers LLM workflows and predictive ML models. You will bridge traditional data architecture with modern AI needs, build scalable pipelines, and guide engineers in best practices.

You will collaborate with data scientists, analysts, and enterprise teams to deliver resilient, cost-effective data solutions across multi-cloud environments.

Qualifications

• Bachelor's degree or higher in Computer Science or related quantitative field.
• At least 6 years of experience in application development.
• At least 4 years of experience in distributed data.
• At least 4 years of experience with SQL.
• At least 4 years of experience programming in Python, Java, or Scala.
• At least 4 years designing and developing data pipelines.
• At least 2 years in data modeling and end-to-end data solutions.

Responsibilities

• Architect, build, and scale data pipelines to supply AI/ML and LLM workflows.
• Lead and mentor engineers; set coding standards and design patterns.
• Collaborate on data governance, security, and data lineage initiatives.
• Develop feature stores for real-time inferencing and offline training.
• Audit and optimize cross-cloud pipelines, queries, and storage costs.
• Partner with PMs, data scientists, and executives to deliver production-ready solutions.

Skills

Python

SQL

Data modeling

Data pipelines

Distributed computing

Education

Bachelor's degree in Computer Science or related quantitative field

Tools

Databricks

Snowflake

Job description

Capital One seeks a senior Data Engineer to design and implement an AI-enabled data ecosystem that powers LLM workflows and predictive ML models. You will bridge traditional data architecture with modern AI needs, build scalable pipelines, and guide engineers in best practices.

You will collaborate with data scientists, analysts, and enterprise teams to deliver resilient, cost-effective data solutions across multi-cloud environments.