Senior Snowflake Database Architect

The ‘Zendesk Analytics Prototyping’ (ZAP) team is chartered to evolve Zendesk’s business intelligence framework with a focus on AI data, measurement, and ROI insights. We build fine-grained, highly curated, contextually rich datasets capturing every facet of Zendesk’s support operations—both human- and AI-driven—and develop measurements and insights that reflect the true value delivered by AI applications to our customers and their end users. Once prototyped and validated, these metrics and insights are operationalized internally and delivered externally through customer-facing reports.

We’re seeking a Senior Snowflake Database Architect with deep expertise in Snowflake data architecture and modeling to lead the design and optimization of Zendesk’s OLAP product data domain.

You’ll partner closely with data engineers, architects, and analytics teams to shape a scalable, performance-driven data foundation, enabling both internal reporting and customer-facing insights. If you thrive on designing enterprise-scale Snowflake solutions, driving best-in-class data models, and fine-tuning systems to deliver high-impact analytics, we want to hear from you.

What you’ll be doing:

• Drive the end-to-end Snowflake Product data architecture, leading efforts to design and maintain OLAP data models that power Zendesk’s internal and customer-facing analytics. You’ll ensure that our Snowflake environment is built to scale for growing data volumes and complex reporting needs.
• Develop best-in-class data models that deliver fast, reliable insights. You’ll apply advanced Snowflake features—such as search optimization, clustering—to maximize performance and minimize costs.
• Guide Product teams on OLAP data architecture, Snowflake best practices and cost-efficient solutions, sharing your deep expertise to elevate the entire Product Development organization. Encourage a culture of design rigor and data excellence throughout.
• Work closely with Data Engineers, Data Scientists, and Product Managers to translate business requirements into robust Snowflake solutions. 
• Oversee data governance, quality, and security measures to guarantee a trustworthy and compliant data environment. You’ll identify and resolve performance bottlenecks while implementing processes for monitoring, alerting, and troubleshooting issues.
• Continuously evaluate and adopt new Snowflake capabilities, refining the stack to keep Zendesk at the forefront of cloud data innovation. You’ll push for automated testing, CI/CD, and other forward-thinking approaches to maintain a future-proof data foundation.

What you bring to the role

Basic Qualifications:

• Bachelor’s degree in Computer Science/Information Systems or related field. 
• 8+ years of experience in data engineering or database architecture, with a proven track record of designing and optimizing Snowflake environments at an enterprise scale
• Expert-level proficiency in Snowflake features and components, such as clustering, micro-partitioning, Streams & Tasks, and performance tuning best practices
• Strong foundation in OLAP data modeling, including Kimball and Inmon methodologies, with the ability to develop robust, scalable schemas for complex analytical use cases
• Strong proficiency in Python, SQL, and other data engineering technologies including DBT, Airflow. Hands-on experience with cloud platforms (AWS preferred), big data tools (e.g. Spark, Hadoop), and distributed systems.
• Ability to work cross-functionally with product teams, data scientists, software engineers, and business leaders. Strong communicator, able to explain technical concepts to non-technical stakeholders.
• Familiarity with data governance principles and best practices, including data quality, data lineage, and security standards.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Master’s degree in Computer Science/Information Systems or related field
• SnowPro Advanced certification
• Familiarity with Lean/6 Sigma principles and an understanding of CRM analytics.

Our Data Stack:

ELT (Snowflake, dbt, Airflow, Kafka)

Infrastructure (AWS, Kubernetes, Terraform, GitHub Actions)

BI (QuickSight, Looker)