As a Sr. Enterprise Data Architect, accountable and responsible for coordinating, documenting, communicating and governing on enterprise Data and Data AI architectures.
Deep understanding of modern cloud data and AI architectures and excellent communication skills to effectively lead and collaborate with various teams and stakeholders.
Assisting in the documentation of target state architectures, guiding principles and frameworks.
May also be involved in training engineers across the enterprise.
Ensuring that all individual solution architecture artifacts and changes are documented as per process standards and stored in T. Rowe Price’s EA Library to facilitate compliance, organization, and access.
Mentoring junior members of the team.
Requirements
A Bachelor's or Master's degree in a technical field
5+ years of experience in data-intensive roles, ideally in Asset Management or a related financial services or highly regulated industry
A proven track record leading the design and architecture of robust, scalable, and secure data solutions on Snowflake and cloud-native platform (preferably AWS)
The ability to provide technical leadership, defining architectural patterns and best practices and driving their adoption across engineering teams
A genuine passion for hands-on engineering; comfortable whiteboarding an architecture as well as prototyping a solution in code
Deep, hands-on expertise with a modern data stack, including AWS, Snowflake, Dagster or like orchestrator, dbt, and Spark, Cortex AI, Snowpark Container services, etc.
A collaborative mindset with excellent communication skills, capable of engaging both technical and non-technical audiences
Tech Stack
AWS
Cloud
Spark
Benefits
Competitive compensation
Annual bonus eligibility
A generous retirement plan
Hybrid work schedule
Health and wellness benefits, including online therapy
Paid time off for vacation, illness, medical appointments, and volunteering days
Family care resources, including fertility and adoption benefits