data architect lead (Seattle, WA)

About the Role

Key Responsibilities

• Creating conceptual, logical, and physical data models to represent how data is structured and used across the enterprise.
• Providing solution architecture for specific business requirements as well as the overall enterprise data ecosystem.
• Developing and providing guidance on enterprise best practices for data ingestion, processing, and integration.
• Establishing policies, standards, and procedures for data quality, security, and access to ensure data integrity and compliance.
• Designing, implementing, and maintaining data lake to support reporting, analytics, AI/ML, and other business requirements.
• Ensuring data from different sources can be seamlessly integrated and accessed.
• Monitoring database/data lake performance and identifying areas for improvement to ensure efficient data access and processing.

Requirements

• In-depth knowledge in architecting and implementing data Lakehouse platforms, including strong experience with Databricks platform and Unity Catalog.
• Experience with data management principles and best practices, including data governance frameworks using Collibra tool.
• Ability to create and manage conceptual, logical, and physical data models, data definitions, and data dictionaries.
• Experience with data modeling tools such as ER Studio.
• Experience in Azure cloud and Databricks platform, AI/ML, reporting, and analytics tools and technologies.
• Eight or more years of architecture, data, and/or IT experience.
• Two or more years of experience in data modeling, engineering, or data transformation.
• Strong communication skills with the ability to convey technical concepts to both technical and non-technical audiences.

Nice to Have

• Knowledge of hub and spoke data architecture and data mesh principles.
• Proficiency in defining and developing ontologies, business taxonomies, and extended object metadata.

Qualifications

• Eight or more years of architecture, data, and/or IT experience.
• Two or more years of experience in data modeling, data engineering, or data transformation.
• Experience with data cataloging and classification.

Benefits & Perks

• Paid parental leave, paid holidays, disability insurance, health insurance, dental insurance, vision insurance, 401(k) matching, life insurance.
• Access to medical, dental, vision, life insurance, short-term and long-term disability, paid parental leave, and other benefits.
• Educational benefits including tuition coverage through the Starbucks College Achievement Plan, student loan management resources, and educational opportunities.
• Backup care, DACA reimbursement, and flexible work arrangements for Seattle area partners.