Principal Data Architect — Databricks Enablement

Accountabilities:

• • Define strategic data and technology roadmaps for customers, translating business objectives into targeted technical outcomes and actionable plans.
  • Serve as a senior data engineering subject matter expert during the definition and planning of upcoming customer engagements.
  • Partner with pre-sales teams to assess customer requirements, shape solution approaches, and contribute technical expertise to proposed engagements.
  • Lead the architecture and design of complex cloud-based data and analytics solutions across diverse customer environments.
  • Establish and oversee data standards, operating procedures, documentation, and repeatable implementation practices.
  • Provide technical guidance and mentorship to Architects and Engineers, helping teams make sound architectural and engineering decisions.
  • Conduct technical interviews for architecture and engineering candidates and contribute to maintaining a strong technical talent bar.
  • Promote consistent, scalable, and well-documented approaches to cloud data engineering across projects and teams.
  • Support the adoption of modern practices spanning data engineering, analytics, machine learning, generative AI, and DataOps.
  • Collaborate with customers and internal stakeholders to identify opportunities for modernization, optimization, and improved data capabilities.

  Requirements:

  • 10+ years of experience designing and building complex data systems, including substantial experience working within cloud data environments.
  • At least 4 years of experience working across the AWS data landscape.
  • Strong expertise across multiple areas of traditional data, including relational database design, optimization and migration; transactional and analytical data modeling; BI dashboards and visualization; data governance; and master data management.
  • Strong expertise across multiple areas of modern data, including Spark and big data processing, streaming, NoSQL, machine learning and MLOps, generative AI, foundational models, and DataOps.
  • Experience with machine learning and MLOps using platforms such as SageMaker is an asset.
  • Experience with generative AI foundational models and associated frameworks, including platforms such as Bedrock.
  • Strong understanding of DataOps practices, including infrastructure as code, data testing, data versioning, and automated delivery.
  • Experience with at least two infrastructure-as-code tools, CI/CD platforms or tools, and/or Python for analytics and automation.
  • Strong drive to standardize, document, and continuously improve technical approaches and solution architectures.
  • Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and business audiences.
  • Strong consulting mindset and ability to operate effectively with customers, pre-sales teams, engineers, architects, and other stakeholders.
  • Ability to provide technical leadership while remaining pragmatic and focused on measurable customer outcomes.
  • Willingness and ability to travel up to approximately 25% depending on business needs.
  • Must be legally authorized to work in Canada without current or future employer-sponsored visa support.

  Benefits:

  • Base salary: CAD $180,000–$202,000 per year, commensurate with experience and qualifications.
  • Potential additional compensation through bonuses, commissions, equity, and other incentives depending on the role and individual or company performance.
  • 100% remote work with a globally distributed team.
  • Equitable Life hybrid benefits plan with 100% premium coverage for employees and dependents.
  • Competitive phantom equity program.
  • Long-term disability coverage.
  • Employer pension contribution with a 4% match.
  • Unlimited vacation, sick leave, paid holidays, and parental leave.
  • Exam and professional certification costs covered.
  • Peer bonus and recognition awards.
  • State-of-the-art laptop and professional tools.
  • Equipment and home-office stipend.
  • Individual professional development planning.
  • Annual learning and development stipend.
  • Opportunity to work with an international team in a collaborative and inclusive environment.