Senior Data Engineer - Cloud Data Platforms & Pipelines

Capital One; McLean (VA); On-site; USD 120,000 - 180,000; Full time

Job summary

Capital One is seeking a Data Engineer 5 to lead cloud-first data solutions in a fast-paced, collaborative environment. You will design end-to-end data pipelines, mentor peers, and influence teams across ML and data platforms to deliver scalable, high-impact adtech and marketing data experiences for millions of Americans.

The role emphasizes independent architectural decisions, modern data lakehouse patterns, and strong SQL/NoSQL skills, with hands-on work in Python and Spark within cloud

Qualifications

• Bachelor's Degree or higher in Computer Science or a 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 with 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 databases

Responsibilities

• Collaborate with and across Agile teams to design, develop, test, implement, and support technical solutions in full-stack development tools and technologies
• Influence a team of developers, data analysts and data scientists with deep experience in machine learning, distributed microservices, lakehouse architecture, and full-stack systems
• Utilize programming languages such as Python and Spark, along with open-source relational and NoSQL databases, and cloud-based data warehousing platforms including Databricks and Snowflake
• Share your passion for staying on top of trends in data, experimenting with and learning new technologies, participating in internal and external technology communities, and mentoring other members of the data community
• Collaborate with product managers and software engineers to deliver robust cloud-first data solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
• Independently design, build and deliver world-class cloud data solutions and applications with little or no support from supervisors or managers
• Architect and enforce common data engineering design patterns to ensure code quality, maintainability, and reusability across data platforms and pipelines
• Serve as an ambassador for the data engineering team, communicating technical concepts and data outcomes clearly to both internal and external stakeholders to drive alignment and shared understanding
• Design and build data pipelines and platforms with a focus on scalability, resilience, and operational efficiency, ensuring robust performance under increasing data volume and business demands
• Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers
• Lead and execute large-scale, transformative data initiatives from end to end, independently driving critical architectural decisions and evaluating platform choices, such as Snowflake versus Databricks, based on technical and business requirements

Education

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

Master's Degree in Computer Science or related field

6+ years of experience in application development

4+ years of experience in distributed data

4+ years of experience with SQL

4+ years of experience programming in Python/Java/Scala

4+ years designing and developing data pipelines

2+ years data modeling with relational and non-relational databases

Tools

Databricks

Snowflake

Spark

Job description

Capital One is seeking a Data Engineer 5 to lead cloud-first data solutions in a fast-paced, collaborative environment. You will design end-to-end data pipelines, mentor peers, and influence teams across ML and data platforms to deliver scalable, high-impact adtech and marketing data experiences for millions of Americans.

The role emphasizes independent architectural decisions, modern data lakehouse patterns, and strong SQL/NoSQL skills, with hands-on work in Python and Spark within cloud