Principal Data Architect — Databricks Enablement

caylent

BRAZIL

Posted Aug 14, 2026

Other
Remote
Cloud Data Engineering

Job description

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

We're looking for a Principal Data Architect with deep Databricks expertise to lead high-visibility data platform engagements for enterprise clients standardizing on Databricks as their unified analytics and AI platform.

This role blends architectural depth with a forward-deployed engineering mentality. You'll help define the guardrails and standards that keep a growing Databricks platform governable at scale, and you'll get hands-on alongside client business and engineering teams to implement their first priority use cases — teaching as you build, so the client can increasingly self-serve. You're equally comfortable designing a semantic layer and sitting next to a client engineer walking them through their first production pipeline.

This role owns the use-case side of Databricks enablement — hands-on delivery with client business and engineering teams, coaching toward self-service, and feeding requirements back to the platform/foundation team — while maintaining architectural awareness of the broader platform.

Your Qualifications

Key Responsibilities:

Define strategic roadmaps and Databricks adoption plans for clients, including platform guardrails, a self-service maturity model, and a use-case prioritization approach, in a consultative capacity
Operate with a forward-deployed engineer mentality: embed directly with client business and engineering teams to implement their highest-priority use cases hands-on, then progressively shift them toward self-service as platform capability matures
Close the loop between "what clients need" and "what the platform supports" — translate needs surfaced during hands-on use-case delivery into concrete feature requests and guardrail requirements for the platform/foundation team
Act as a data engineering SME in pre-sales and scoping conversations, shaping engagement approach and staffing alongside pre-sales teams
Coach and upskill client architects, engineers, and business-embedded technologists on Databricks best practices, patterns, and self-service tooling
Oversee development of data standards, operating procedures, and semantic/lineage layers that keep a Databricks environment governable as adoption scales across business units
Perform technical interviews for Architect and Engineer candidates; provide technical guidance and mentorship across the practice
Build trusted relationships with client technical and business leadership, balancing platform governance against business teams' desire for speed and autonomy

Required Technical Qualifications

10 years of experience designing and building complex data systems, including experience in these areas:
- Relational database design, optimization and migration
- Data modeling for both transactional and analytics systems, including implementation of industry-standard data models
- BI dashboards and visualizations
- Data governance and MDM
- Big data processing using Spark, streaming solutions, and NoSQL
- Machine learning and MLOps
- GenAI foundational models, along with the approaches and frameworks used with them
- DataOps practices (Infrastructure as Code, data testing, data versioning, etc.)
Deep, hands-on Databricks experience — workspace/persona architecture, Unity Catalog, lakehouse design patterns, job orchestration, and Databricks-native governance and AI/ML tooling.
Demonstrated forward-deployed or embedded-delivery experience: comfortable building alongside a client team early in an engagement, then handing off to self-service as maturity increases.
Experience with at least two of: Infrastructure as Code tools (Terraform preferred), CI/CD pipelines and tools, Python for analytics (numpy, pandas, matplotlib, etc.) and automation.
Strong drive toward standardizing and documenting our approach and solutions
Excellent written and verbal communication skills; high tolerance for ambiguity

Experience Requirements

At least 4 years of experience in the AWS data landscape
5+ years of deep, hands-on Databricks experience
High business acumen — able to translate ambiguous asks from non-technical business stakeholders into scoped technical work, and to communicate trade-offs clearly to both engineers and VP-level leadership

Preferred Qualifications

Prior experience in a "platform + use-case" hub-and-spoke delivery model, including feeding platform feedback loops from hands-on delivery work
Background in consulting, systems integration, or professional services
Familiarity with SOW-based, time-and-materials delivery and scope management

Benefits

100% remote work
Generous holidays and flexible PTO
Competitive phantom equity
Paid for exams and certifications
Peer bonus awards
State of the art laptop and tools
Equipment & Office Stipend
Individual professional development plan
Annual stipend for Learning and Development
Work with an amazing worldwide team and in an incredible corporate culture

This role may require up to 25% travel, depending on business needs.

NOTE: We’re unable to provide visa sponsorship now or at any time in the future.

At Caylent, we are committed to fair, transparent, and inclusive hiring practices. As part of our recruitment process, we may use artificial intelligence (AI) tools or automated systems to assist with the screening and evaluation of applications to help match candidate qualifications with job requirements.
These tools are designed to support — not replace — human decision-making. Final hiring decisions are always made by our trained recruitment professionals.
If an AI or automated tool is used during your application process, it will only be in accordance with applicable laws and regulations, and your information will be handled in a secure and confidential manner.
If you have any questions, please contact talent@caylent.com

Caylent is a place where everyone belongs. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.

We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com.