Why This Role Stands Out
This hybrid Data Architect role offers a unique opportunity to shape the future of enterprise data capabilities in a growing organization, leveraging AWS and Snowflake to drive AI initiatives and establish best practices. You'll thrive here if you have a strong background in designing scalable cloud-based data platforms and enjoy collaborating with leaders to define strategic roadmaps, making this an excellent position for impactful career growth.
Quick Overview
Seniority
Mid Senior
Work mode
Hybrid
Location
Richardson, TX, United States
Posted
6 weeks ago
AWSSnowflake
Job Description
We are seeking a Senior Data Architect to help drive the next generation of enterprise data capabilities within a rapidly growing, newly centralized data organization. This role will play a key part in designing and implementing modern data architectures, data products, and strategic roadmaps that support enterprise-wide analytics, reporting, and AI initiatives.
In this highly visible position, you will partner directly with business leaders, engineering teams, and data stakeholders to define data strategy, architect scalable solutions, and establish best practices across a modern AWS and Snowflake ecosystem. This is an opportunity to influence the future-state data platform from the ground up within a highly collaborative and strategic environment.
Required Skills & Experience
In this highly visible position, you will partner directly with business leaders, engineering teams, and data stakeholders to define data strategy, architect scalable solutions, and establish best practices across a modern AWS and Snowflake ecosystem. This is an opportunity to influence the future-state data platform from the ground up within a highly collaborative and strategic environment.
Required Skills & Experience
- Strong experience designing enterprise Data Architectures, Data Warehouses, and scalable cloud-based data platforms
- Deep expertise with AWS and Snowflake, including warehouse sizing, clustering, partitioning, and performance optimization
- Experience developing data roadmaps, architecture standards, and long-term data strategies
- Strong understanding of data ingestion patterns, data integration frameworks, and modern data engineering practices
- Experience with AI-enabled data architectures and emerging AI technologies
- Knowledge of RAG (Retrieval-Augmented Generation), Vector Databases, MCP, and Large Language Models (LLMs)
- Experience building data products and supporting advanced analytics initiatives
- Financial services, banking, or regulated industry experience
- Design and implement enterprise data architectures leveraging AWS and Snowflake
- Define data platform strategy, roadmaps, and best practices in partnership with business and technology leaders
- Architect scalable data ingestion, storage, governance, and analytics solutions
- Evaluate and incorporate emerging AI technologies and data products into the organization's long-term vision
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