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As a Distinguished Engineer at Capital One, you will be a part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Distinguished Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while driving towards strong technology solutions.
Job Responsibility:
Define and champion the strategic roadmap for the adoption, governance, and cost-optimization of the data ecosystem leveraging Databricks and Snowflake on the AWS cloud.
Lead the design and implementation of highly scalable, fault-tolerant, and cost-effective data architectures that seamlessly integrate Databricks (for complex processing/ML) and Snowflake (for warehousing/BI).
Serve as the primary technical authority for data security and governance best practices within Databricks and Snowflake, ensuring integration with core AWS security services (e.g., IAM, KMS).
Drive performance engineering and optimization for large-scale data ingestion and processing workloads across the Databricks/Snowflake/AWS data pipeline.
Mentor engineering teams on the advanced features, architecture, and cost-efficient usage of Databricks, Snowflake, and related AWS services.
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
Ensure Code is of the highest quality & standard while being an active contributor and reviewer on critical repos of the application
Develop full stack applications with a product engineering mindset, spanning frontend and backend ecosystems that balance simplicity with flexibility
Requirements:
Bachelor’s Degree
At least 7 years of experience in Software engineering and solution architecture
At least 7 years of experience in Enterprise architecture and design patterns
At least 5 years of experience in Cloud computing (AWS, Microsoft Azure, Google Cloud)
At least 5 years of experience in Security engineering and architecture
At least 5 years of experience in Data architecture including Event Driven and Real-Time architectures
Nice to have:
Bachelor's or Master's Degree in Computer Science or a related field.
10+ years of hands-on experience developing and architecting solutions on AWS.
Deep proficiency and strategic experience with Databricks (e.g., Delta Lake, Unity Catalog, MLflow, performance tuning Spark workloads).
Deep proficiency and strategic experience with Snowflake (e.g., Data Sharing, Snowpipe, external tables, security features, cost governance, advanced SQL/Stored Procedures).
Deep practical knowledge of core AWS data services such as Amazon S3, EMR, Glue, Kinesis, and Lambda, and how they integrate with Databricks and Snowflake.
Experience with Infrastructure as Code (IaC) tools (e.g., Terraform) to automate the deployment and management of Databricks and Snowflake environments on AWS.
Relevant professional certifications such as AWS Certified Solutions Architect - Professional or Snowflake/Databricks certifications (e.g., Certified SnowPro Advanced Architect).
10+ years of professional experience coding in commonly used languages like Java, Python, Go, JavaScript/TypeScript, Swift, etc.
8+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support.
Experience in applying Artificial Intelligence or Machine Learning concepts to engineering challenges (e.g., anomaly detection, test optimization, intelligent testing).
Deep practical knowledge of Site Reliability Engineering (SRE) principles, chaos engineering, and advanced Observability tooling (e.g., OpenTelemetry, Prometheus, Tracing).
Experience in implementing Artificial Intelligence or Artificial Intelligence-enabled solutions.
What we offer:
performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being