Data Engineer 5 (Python, SQL, Databricks, Snowflake) (Enterprise Platforms Technology)

Capital One • McLean, VA

7d • $209,000 - $286,200

About The Position

We are seeking a Data Engineer to develop the technical vision, architectural design, and implementation of our AI-enabling data ecosystem. In this strategic role, you will bridge the gap between traditional enterprise data architecture and modern AI capabilities. You will design resilient, scalable data pipelines, and real-time streaming architectures that power LLM workflows, Retrieval-Augmented Generation (RAG) pipelines, and predictive ML models. You will work closely with Data Scientists, Analysts, and other Engineers to establish best-in-class data engineering practices for traditional and AI enabled workloads.

Requirements

• Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 6 years of experience in application development (Internship experience does not apply)
• At least 4 years of experience in distributed data
• At least 4 years of experience with SQL
• At least 4 years of experience programming with at least one of the following languages: Python, Java, or Scala
• At least 4 years of experience designing and developing data pipelines
• At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems

Nice To Haves

• Master's Degree in a related field
• 9+ years of experience in application development including Python, SQL, Scala, or Java
• 5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
• 5+ year experience working on real-time data and streaming applications
• 5+ years of data warehousing experience (eg Snowflake)
• Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion (Claude, Gemini)

Responsibilities

• Architect, build, and scale clean, reliable, and latency-optimized data pipelines (batch and real-time) designed specifically to supply structured, semi-structured, and unstructured data to AI/ML applications and Large Language Models (LLMs).
• Contribute to defining the architectural blueprint for the Top of House AI data layer. Serve as a hands-on technical lead, guiding junior and mid-level engineers in coding standards, design patterns, and engineering excellence.
• Partner with Enterprise Security and Data Governance teams to implement robust data classification, privacy safeguards, and automated lineage tracking for AI models and training datasets.
• Build and maintain scalable feature stores to support both real-time inferencing and offline model training across executive-facing predictive models.
• Audit and optimize cross-cloud data pipelines, query performance, and storage infrastructure for efficiency, cost management, and reliability.
• Partner directly with Technical Program Managers, Data Scientists, Top of House leads, and C-suite stakeholders to turn executive data needs into production-ready solutions.

Benefits

• performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

What This Job Offers

• Job Type: Full-time
• Career Level: Senior