Databricks Solution Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design scalable architectures for Databricks solutions utilizing Lakehouse, Delta Lake, and Unity Catalog patterns.

• Facilitate technical discovery workshops focused on customer objectives, data challenges, and existing architecture.

• Create functional prototypes, proofs-of-concept, and reference architectures.

• Advise customers on best practices for data pipelines, data modeling, and platform governance.

• Provide guidance on integrating Databricks with AWS, Azure, GCP, and related data tools.

• Showcase Databricks capabilities across Data Engineering, Data Science, Machine Learning, and Generative AI use cases, including Mosaic AI, MLflow, and Feature Store.

• Identify and mitigate technical risks to assist delivery teams effectively.

• Translate intricate technical concepts into tangible business value for technical stakeholders and executives.

• Collaborate with account teams during the sales process to shape technical strategies.

• Work alongside Data Scientists and ML Engineers on AI-driven demo assets and reference architectures.

• Act as a resident expert on Databricks and empower the wider team.

• Contribute to reusable accelerators, demo assets, and technical playbooks.

• Keep abreast of Databricks releases and emerging data and AI patterns.

• Represent BIG at customer events, webinars, and Databricks partner activities.

• Provide field insights to Databricks product and partner teams.

• Travel up to 15% for customer meetings and partner collaborations.

⛳️ Requirements

• Over 3 years of hands-on experience with Databricks and/or Snowflake in a technical role.

• More than 5 years in customer-facing technical positions — solutions architecture, technical consulting, or sales engineering.

• Proven experience in designing, presenting, and delivering production data architectures for enterprise clients, including Lakehouse, Delta Lake, and Unity Catalog patterns, on AWS, Azure, and/or GCP.

• Databricks Professional-level certification, such as Data Engineer Professional or Machine Learning Professional.

• Strong proficiency in at least one core data domain: big data engineering (Spark, Kafka), Data Warehousing & ETL, or Data Science & ML.

• Proficient in Python and SQL.

• Excellent verbal and written communication and presentation abilities.

• Capability to engage in and lead business-level discussions with both technical and non-technical client and internal team members.

• Ability to convert complex topics into clear business value and gain buy-in from both engineers and executives.

• Preferred: a degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative discipline.

• Preferred: experience with dbt, Fivetran, Airflow, or Delta Sharing.

• Preferred: familiarity with AI/GenAI frameworks and LLM application patterns.

• Preferred: Databricks GenAI Engineer Associate certification.

• Preferred: exposure to enterprise engagement cycles and understanding how technical decisions influence deal outcomes.

• Preferred: experience with Frontier LLMs such as Claude Code for SDLC acceleration.

🏝️ Benefits

• Globally recognized as a Great Place to Work.

• Access to over 10 cutting-edge technology practices and ongoing learning opportunities.

• Competitive compensation and benefits package.

• Flexible, remote-friendly work environment.

• Engaging, high-impact data and AI projects for enterprise clients.

• A team that celebrates successes together.