Senior Data Architect

EchoStar•Centennial, CO

6d•Onsite

About The Position

Modernizing and scaling enterprise data infrastructure requires sophisticated architecture that bridges traditional data modeling with contemporary lakehouse frameworks. This role resolves complex data fragmentation, storage tiering inefficiencies, and compute cost overruns across cloud environments to establish performant, enterprise-grade data assets. Crucially, this work unlocks advanced AI capabilities by designing architectures for unstructured data, vector databases, Retrieval-Augmented Generation (RAG), and semantic layers. Through cross-functional governance and technical leadership, enterprise data assets become securely managed, highly scalable, and fully aligned with strategic goals.

Requirements

Advanced AI Application expertise; leveraging unstructured data frameworks, vector databases, and Retrieval-Augmented Generation (RAG) within modern data architectures
Critical experience in designing multi-tier enterprise data structures, Medallion patterns, and high-performance data lakehouse architectures
Strong skills in data modeling, schema design, and versioning within multi-modeler repository environments
Critical experience in cloud warehouse cost optimization, cluster compute tuning, and query performance enhancement
Expertise in data governance, fine-grained access control (ABAC), data lineage, and compliance standards such as CPNI, CCPA, and SOC2
Exceptional problem solving, collaboration, and cross-functional decision-making capabilities across technical and business stakeholders
Minimum Education: Bachelor's degree in a technical discipline, preferably in Computer Science or Software Engineering, or equivalent combination of education and experience
Minimum Experience: 10 years of continuous data architecture and data modeling experience; with at least 3 recent years leading primary data architecture design and implementation in a VLDB / MPP environment
2 years of experience with Azure, AWS, or GCP cloud environments
1 year of experience with Databricks & Genie and/or Snowflake & Cortex
1 year of experience with orchestration tools such as Apache Airflow or Control-M

Nice To Haves

Preferred industry certifications including Snowflake Certified Architect, Databricks Professional, or AWS Data Engineer

Responsibilities

Establish and maintain corporate data model design principles; integrating Kimball and Inmon methodologies with Medallion Lakehouse patterns to deliver performant data assets
Architect scalable frameworks and storage tiering to support AI initiatives; including vector databases, Retrieval-Augmented Generation (RAG), and enterprise semantic layers
Lead efforts in optimizing query execution, cluster compute, and cloud warehouse costs across enterprise platforms
Partner with enterprise architects, data engineering, and business analysis teams to enforce data governance standards and execute data SDLC phases
Define data integration solutions and mitigate infrastructure risks to deliver scalable, highly available enterprise data architecture