Zendesk is hiring a Principal Engineer – Data Platform Architecture to own and shape the architecture of the Zendesk Data Platform (ZDP). You will ensure the platform is performant, reliable, secure, and cost-optimized at scale, while setting technical direction for data ingestion, management, and consumption on cloud-scale OLAP platforms. This hands-on technical leadership role involves architecting high-impact data systems and advising on strategic trade-offs.

What You'll Do

Own the end-to-end architecture of the Zendesk Data Platform (ZDP) to support internal analytics and customer-facing analytics solutions.
Ensure ZDP supports strategic business needs while meeting standards for scalability, reliability, and cost-effectiveness.
Lead solution architecture for data ingestion, transformation, governance, and delivery—spanning batch, streaming, and near-real-time scenarios.
Serve as a technical authority on Snowflake, including advanced features such as Snowpark, Snowpipe, and Cortex.
Advise product and engineering leads on data modeling, access policies, and query optimization strategies.
Establish engineering best practices for cost monitoring, performance tuning, security, and regulatory compliance across all Data Platform services.
Guide teams in making architectural trade-offs between compute frameworks, storage design, clustering strategies, and pattern optimizations.
Act as a cross-functional consultant—communicating complex architecture to stakeholders, mediating divergent viewpoints, and driving alignment.
Ensure all architectural decisions align with requirements for privacy, auditability, governance, and operational excellence.
Provide mentorship to staff and senior engineers, cultivating a culture of technical rigor, growth, and collaboration.

What We're Looking For

10+ years of experience in large-scale data engineering or analytics infrastructure roles, with at least 3 years at principal or staff-level solution architecture.
Deep hands-on expertise with Snowflake, including architecture, implementation, performance optimization, and advanced features (Snowpark, Snowpipe, Cortex, Native Apps, external functions, secure sharing).
Extensive practical knowledge of OLAP warehousing concepts, modern data modeling strategies, and design for cost-effective, performant analytics.
Strong architectural judgment across ETL/ELT, batch and streaming, real-time pipelines, and data access patterns.
Demonstrated ability to lead technical design reviews, drive technical alignment across multiple engineering teams, and influence data & analytics product strategy.
Experience optimizing for multi-instance architectures, with a clear understanding of compliance, privacy, and data lifecycle management in a cloud platform context.
Fluency in SQL and data engineering languages (Python, Java or similar).
Ability to navigate and influence in a complex, matrixed organization—translating technical depth into strategic direction for diverse stakeholders.
Familiarity with regulatory frameworks and audit/compliance implications for enterprise data platforms (e.g., SOC 2, GDPR, HIPAA).

Nice to Have

Hands-on architectural leadership migrating or evolving enterprise-scale data platforms to cloud-native OLAP solutions (Snowflake, BigQuery, Redshift, etc).
Experience integrating Snowflake with event-driven architectures (Kafka, Kinesis, Pub/Sub).
Prior experience with customer-facing analytics products and platform integration challenges.
Contributions to internal or external data platform communities and thought leadership.

Technical Stack

Snowflake, Snowpark, Snowpipe, Cortex
SQL, Python, Java
Kafka, Kinesis, Pub/Sub, Spark

Team & Environment

You will work alongside data, analytics, and product engineering groups.

Benefits & Compensation

Compensation range: $228,000.00-$342,000.00

Work Mode

This role follows a hybrid work model.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster global diversity, equity, & inclusion in the workplace. Individuals seeking employment and employees at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law.