Description:
About the team: In this role, you will work with our Card Data Architecture team to provide world-class data experiences that our end users love. You'll be a key player in building and shaping the future of our data infrastructure, leveraging next-generation technologies like Generative AI and Machine Learning to solve some of the hardest problems in the financial sector – all at Capital One scale.
We're passionate about finding innovative solutions while maintaining a strong governance practice and ensuring data observability. If you are ready to provide thought leadership and build engineering excellence across Capital One's engineering teams, come join us in our mission to change banking for good.
Key responsibilities:
- Articulate and evangelize a bold technical vision for your domain
- Decompose complex problems into practical and operational solutions
- Ensure the quality of technical design and implementation
- Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability
- Continue learning and injecting advanced technical knowledge into our community
- Handle several projects simultaneously, balancing your time to maximize impact
- Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community
- Have a software engineering/problem solving mindset being equally comfortable with deep diving on real time and batch data pipelines, with an understanding of how to build highly resilient operational platforms that can scale to 50k+ TPS with 4 9’s availability.
- In-depth knowledge of handling large data pipelines to clean, transform , and observe data.
- General understanding of Machine Learning principles and generative AI
- Operate with a platform mindset with deep familiarity on multi-tenancy, serverless computing, high performance computing patterns
Basic Qualifications:
- Bachelor’s Degree
- At least 7 years of experience in Data Engineering
Preferred Qualifications:
- Masters’ Degree
- 8+ years of experience in developing production-grade data pipelines for big data needs
- 10+ years of experience in microservices, real time API development for distributed operational systems
- 8+ years of experience in cloud native platforms ( EventBridge, Fargate, lambdas, DynamoDB).
- Experience with modern data platform strategies (Data Mesh, Data Fabric)