Lead Data Engineer - Data Transformation (Modeling and Architecture)

Capital One is seeking a Lead Data Engineer for Data Transformation (Modeling and Architecture) to design scalable data models, govern data assets, and craft AI ready architectures across Data Lake and Data Warehouse ecosystems on cloud platforms. This onsite role is based in Richmond, VA.

Responsibilities

• Design and maintain comprehensive data models across conceptual, logical, and physical layers to ensure scalable architecture and strong data integrity across enterprise systems.
• Lead the development of the organization’s data landscape using Consumer Driven design principles to reflect business realities and evolving needs.
• Architect and implement robust data ecosystem solutions, including Data Lake and Data Warehouse patterns, to support diverse analytical and operational requirements.
• Support high performance data pipelines and complex transformations using SQL, Spark, and Python to efficiently process large-scale datasets.
• Define and enforce rigorous data governance standards while managing metadata frameworks to ensure data compliance and discoverability.
• Translate complex technical concepts into actionable business insights, taking the lead on initiatives and collaborating with stakeholders to meet organizational goals.
• Contribute to the evolution of the data ecosystem by designing AI ready architectures.
• Collaborate across Agile teams to design, develop, implement, and support technical solutions.
• Work with a team of developers experienced in machine learning, AI, distributed microservices, and full stack systems.
• Share a commitment to staying current with tech trends, experimenting with new technologies, participating in internal and external technology communities, and mentoring other engineers.
• Collaborate with digital product managers and deliver robust cloud based solutions that empower millions of Americans to achieve financial empowerment.

Requirements

• Bachelor’s Degree
• At least 4 years of experience in application development (internship experience does not apply)
• At least 2 years of experience in big data technologies
• At least 1 year of experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Basic Qualifications

• Bachelor’s Degree
• At least 4 years of experience in application development (internship experience does not apply)
• At least 2 years of experience in big data technologies
• At least 1 year of experience with cloud computing (AWS, Microsoft Azure, Google Cloud)

Preferred Qualifications

• 4+ years of experience in Data Architecture / Data Modeling
• 7+ years of experience in application development including Python, SQL, Scala, or Java
• 4+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
• 4+ years of experience with distributed data / computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
• 4+ years of experience working on real-time data and streaming applications
• 4+ years of experience with NoSQL implementations (Mongo, Cassandra)
• 4+ years of data warehousing experience (Redshift or Snowflake)
• 4+ years of experience with UNIX / Linux including basic commands and shell scripting
• 2+ years of experience with Agile engineering practices
• Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion

Technologies

• SQL
• Spark
• Python
• Scala
• Java
• MapReduce
• Hadoop
• Hive
• EMR
• Kafka
• Gurobi
• MySQL
• MongoDB
• Cassandra
• Redshift
• Snowflake
• AWS
• Microsoft Azure
• Google Cloud
• UNIX / Linux
• Shell scripting
• Data Lake
• Data Warehouse

Benefits

• Health benefits
• Financial benefits
• Performance-based incentives (cash bonuses and/or long-term incentives)