Principal Data Architect — Databricks Enablement
New
C
CaylentCloud Services, AI
We are a fully remote global company with employees in Canada, the United States, and Latin America.Full-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 10+ years of experience designing and building complex data systems, including at least 4 years in the AWS data landscape and 5+ years of deep, hands-on Databricks experience.
- Required Skills
- AWSPythonMachine LearningData engineeringSparkTerraformData modelingDatabricks
Requirements
- 10 years of experience designing and building complex data systems.
- 5+ years of deep, hands-on Databricks experience (Unity Catalog, lakehouse patterns, job orchestration).
- 4+ years of experience in the AWS data landscape.
- Expertise in relational database design, optimization, and migration.
- Experience with data modeling for transactional and analytics systems.
- Proficiency in big data processing (Spark, streaming, NoSQL).
- Knowledge of machine learning, MLOps, and GenAI foundational models.
- Experience with DataOps practices including Infrastructure as Code and data versioning.
- Demonstrated experience in forward-deployed or embedded-delivery consulting roles.
- Experience with at least two of: Terraform, CI/CD pipelines, or Python for analytics (numpy, pandas, matplotlib).
- High business acumen with the ability to communicate trade-offs to VP-level leadership.
Responsibilities
- Define strategic roadmaps and Databricks adoption plans for clients, including platform guardrails and self-service maturity models.
- Embed directly with client business and engineering teams to implement high-priority use cases hands-on.
- Transition client teams toward self-service models as platform capability matures.
- Translate client needs into concrete feature requests and requirements for internal platform and foundation teams.
- Act as a data engineering SME in pre-sales and scoping conversations to shape engagement and staffing.
- Coach and upskill client architects and engineers on Databricks best practices and self-service tooling.
- Oversee development of data standards, operating procedures, and semantic/lineage layers for platform governance.
- Perform technical interviews for engineering candidates and provide mentorship across the practice.
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