Lead Data Engineer - Data Transformation (Modeling and Architecture)
About The Position
Lead Data Engineer - Data Transformation (Modeling and Architecture) 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. As a Capital One Lead Data Engineer, you’ll have the opportunity to be on the forefront of driving a major transformation within Capital One.
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 experience with cloud computing (AWS, Microsoft Azure, Google Cloud)
Nice To Haves
- 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 experience with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL)
- 4+ year experience working on real-time data and streaming applications
- 4+ years of experience with NoSQL implementation (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, utilizing capabilities beyond basic code completion
Responsibilities
- Design and maintain comprehensive data models—spanning conceptual, logical, and physical layers—to ensure scalable architecture and high data integrity across enterprise systems.
- 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 that utilize SQL, Spark, and Python to process large-scale datasets efficiently.
- 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, working independently to lead initiatives and collaborate with stakeholders to meet organizational goals.
- Contribute to the evolution of the data ecosystem by designing AI-ready architectures
- Collaborate with and across Agile teams to design, develop, implement, and support technical solutions
- Work with a team of developers with deep experience in machine learning, AI, distributed microservices, and full stack systems
- Share your passion for staying on top of tech trends, experimenting with and learning new technologies, participating in internal & external technology communities, and mentoring other members of the engineering community
- Collaborate with digital product managers, and deliver robust cloud-based solutions that drive powerful experiences to help millions of Americans achieve financial empowerment
Benefits
- comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
