Databricks Solution Architect
Accountabilities: The Databricks Solution Architect will be responsible for designing scalable data and AI architectures, supporting customer engagements, and providing technical leadership throughout solution development. This role requires strong architecture skills, customer-facing experience, and the ability to connect advanced technology solutions with business objectives.
Design scalable Databricks solution architectures based on Lakehouse, Delta Lake, and Unity Catalog patterns aligned with customer needs.
Lead technical discovery sessions to understand business objectives, data challenges, and existing technology environments.
Develop prototypes, proofs of concept, and reference architectures to demonstrate data and AI platform capabilities.
Guide customers on data engineering best practices, data modeling, governance, and platform optimization.
Advise on Databricks integrations with cloud platforms such as AWS, Azure, and GCP, as well as related data technologies.
Demonstrate solutions across data engineering, data science, machine learning, and generative AI use cases.
Collaborate with account teams throughout the sales lifecycle to develop effective technical strategies and support successful customer outcomes.
Identify technical risks and provide recommendations to ensure smooth implementation and delivery.
Translate complex technical concepts into clear business value for technical and executive stakeholders.
Partner with data scientists and ML engineers to create AI-powered demonstrations and reusable solution assets.
Serve as a Databricks subject matter expert by sharing knowledge, creating technical resources, and supporting internal teams.
Stay current with platform developments, emerging data patterns, and AI innovations.
Represent the organization in customer meetings, technical events, webinars, and partner activities.
Provide feedback and insights to improve technical offerings and solution strategies.
Travel occasionally (up to 15%) for customer engagements and partner collaboration.
Requirements:
The ideal candidate is an experienced data and cloud architecture professional with strong Databricks expertise and a passion for designing innovative enterprise solutions. The successful candidate combines technical depth, consulting skills, and the ability to communicate effectively with both technical and business audiences.
3+ years of hands-on experience working with Databricks and/or Snowflake in a technical role.
5+ years of experience in customer-facing technical positions such as solutions architecture, technical consulting, or sales engineering.
Proven experience designing and delivering enterprise data architectures using Lakehouse, Delta Lake, and Unity Catalog patterns.
Experience working with cloud platforms including AWS, Azure, and/or GCP.
Databricks Professional-level certification, such as Data Engineer Professional or Machine Learning Professional.
Strong expertise in at least one core data domain, including big data engineering (Spark, Kafka), data warehousing and ETL, or data science and machine learning.
Strong programming skills in Python and SQL; experience with Scala, Java, or R is an advantage.
Excellent communication, presentation, and stakeholder management skills.
Ability to explain complex technical concepts and demonstrate business value to both engineers and executives.
Experience with technologies such as dbt, Fivetran, Airflow, or Delta Sharing is a plus.
Familiarity with AI/GenAI frameworks, LLM application patterns, or AI engineering practices is preferred.
Experience with Databricks GenAI certifications or similar AI-focused credentials is an advantage.
Exposure to enterprise sales cycles and technical decision-making processes is beneficial.
Bachelor’s degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field is preferred.
Benefits:
Remote-friendly work environment within Canada.
Opportunity to work on impactful data, cloud, and AI transformation projects for enterprise customers.
Exposure to cutting-edge technologies across data engineering, machine learning, and generative AI.
Collaboration with global teams across multiple regions.
Access to continuous learning opportunities and advanced technology practices.
Competitive compensation and comprehensive benefits package.
Supportive, collaborative culture focused on innovation and professional growth.
Opportunity to contribute to technical communities, reusable solutions, and industry-leading practices.
How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?
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