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!
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 QualificationsKey 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
- 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
- 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
- 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
- 100% remote work
- Medical Insurance for you and eligible dependents
- 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 [email protected]
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 [email protected].Skills Required
- 10 years designing and building complex data systems (relational DB design, data modeling, BI, data governance, MDM)
- Experience with big data processing using Spark, streaming solutions, and NoSQL
- Machine learning and MLOps experience, including GenAI foundational model approaches
- Deep, hands-on Databricks experience (workspace/persona architecture, Unity Catalog, lakehouse patterns, job orchestration, native governance and AI/ML tooling)
- Forward-deployed/embedded delivery experience (build alongside client teams and transition to self-service)
- Experience with at least two of: Infrastructure as Code (Terraform preferred), CI/CD pipelines/tools, Python for analytics (numpy, pandas, matplotlib)
- At least 4 years experience in the AWS data landscape
- 5+ years deep, hands-on Databricks experience
- High business acumen; translate ambiguous business asks into scoped technical work and communicate trade-offs to leadership
- Strong written and verbal communication skills; tolerance for ambiguity
- Prior experience in a platform + use-case hub-and-spoke delivery model
- Background in consulting, systems integration, or professional services
- Familiarity with SOW-based, time-and-materials delivery and scope management
What We Do
Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using AWS. We are living in a software-defined world where technology is at the core of every business. To thrive in this paradigm, organizations need to empower their people and processes through technology. Caylent is uniquely positioned to fuel that engine of innovation by bringing ambitious ideas to life for our customers.
