Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)

Capital One Shopping Tech, Data Engineer 5 (Remote- Eligible)

Job Description

Do you love building and pioneering in the technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who solve real problems and meet real customer needs. We are seeking Data Engineers who are passionate about marrying data with emerging technologies. In this role, you’ll be at the forefront of driving a major transformation across Capital One.

What You’ll Do

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

Basic Qualifications

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

Preferred Qualifications

Master’s Degree in Computer Science or a related field