Data Architect

Caylent is an AI-first cloud services company that helps organizations turn ambitious ideas into meaningful business impact. As an AWS Premier Tier Services Partner and a charter member of Anthropic’s Claude Partner Network, we combine deep expertise in AWS, artificial intelligence, and Anthropic’s Claude platform to help customers modernize their technology, build intelligent products, and move AI from experimentation into production.

Our capabilities span generative and agentic AI, cloud migration and modernization, cloud-native application development, data and analytics, DevOps, managed services, security and compliance, and customer experience transformation. At Caylent, our people always come first.

We are a fully remote global company with employees in Canada, the United States and Latin America. We celebrate the culture of each of our team members and foster a community of technological curiosity. Come talk to us to learn more about what it means to be a Caylien!

The Mission

Architect responsible for designing and hardening enterprise-scale Databricks data platforms within client engagements — building the guardrails, automation, and standards that let a growing number of business teams safely build on the platform without it collapsing into unmanaged "click-ops."

Architects maintain primary depth in one core area (Data Platform Development or Data Migration & Modernization) while maintaining architectural awareness across both. Databricks depth is expected regardless of focus area.

Your Qualifications

Key Responsibilities:

• Lead architectural design for Databricks-based data platforms or modernization programs, including workspace consolidation, permissioning/persona models, and configuration-as-code patterns
• Databrick platform designs align with AWS leading-practice architecture patterns (as we are AWS centric)
• Design of high-volume batch and real-time streaming pipelines leveraging PySpark and Structured Streaming (aka Apache Spark)
• Design and integration of Databrick Unity catalog with third party metadata repositories (e.g., AWS Glue Catalog, Snowflake Horizon)
• Design and implement automation (ConfigOps), CI/CD, and guardrail patterns that let business teams safely extend the platform without compromising governance
• Build and maintain certified data products, a semantic layer, and lineage/metadata exposure so the platform can support both self-service and, eventually, agent-driven use cases
• Ensure technical viability, scalability, and production readiness of platform components
• Communicate architectural decisions and trade-offs clearly to both technical and business stakeholders; produce architectural documentation, assessments, and roadmaps