Databricks Solution Architect

• Design scalable Databricks solution architectures — Lakehouse, Delta Lake, and Unity Catalog patterns - tailored to each customer's environment and business goals.
• Lead technical discovery workshops to understand customer business objectives, data challenges, and current-state architecture
• Build working prototypes, proofs-of-concept, and reference architectures that showcase the capabilities of the Databricks Lakehouse Platform.
• Guide customers on best practices for data pipelines, data modeling, and platform governance.
• Advise on integrating Databricks with hyperscaler environments (AWS, Azure, GCP) and adjacent data tooling.
• Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI use cases, including Mosaic AI, MLflow, and Feature Store.
• Identify and mitigate technical risks early so delivery teams are set up for success.
• Translate complex technical concepts into clear business value for both technical stakeholders and executive audiences.
• Partner with account teams throughout the sales process – from early prospect conversations through evaluation – to shape sound, winning technical strategies
• Collaborate with Data Scientists and ML Engineers to develop AI-powered demo assets and reference architectures.

• Serve as a resident Databricks expert within BIG — sharing knowledge and enabling the broader team.
• Contribute reusable accelerators, demo assets, and technical playbooks.
• Stay current on Databricks platform releases and evolving data and AI patterns.
• Represent BIG at customer events, webinars, and Databricks partner activities.
• Provide field feedback to Databricks product and partner teams to help influence the roadmap.
• Travel up to 15% for customer meetings and partner collaboration.

• 3+ years of hands-on experience with Databricks and/or Snowflake in a technical capacity.
• 5+ years in customer-facing technical roles — solutions architecture, technical consulting, or sales engineering.
• Experience designing, presenting, and delivering production data architectures for enterprise customers – including Lakehouse, Delta Lake, and Unity Catalog Patterns – on AWS, Azure, and/or GCP.
• Databricks Professional-level certification (e.g., Data Engineer Professional, Machine Learning Professional).
• Strong expertise in at least one core data domain: big data engineering (Spark, Kafka), Data Warehousing & ETL, or Data Science & ML.
• Fluency in Python and SQL (Scala, Java, or R is a plus).
• Exceptional verbal and written communication and presentation skills - able to engage in and lead business-level meetings with technical and non-technical Client and internal team members.
• Ability to translate complex topics into clear business value and earn buy-in from engineers and executives.

Nice to Have

• A degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field.
• Experience with adjacent technologies such as dbt, Fivetran, Airflow, or Delta Sharing.
• Familiarity with AI/GenAI frameworks and LLM application patterns.
• Databricks GenAI Engineer Associate certification.
• Exposure to enterprise engagement cycles and how technical decisions shape deal outcomes.
• Experience with Frontier LLMs such as Claude code for SDLC acceleration.

Why Bits In Glass?

• Work on meaningful, high-impact data and AI projects for enterprise clients across Canada, the US, UK, and India.
• Join a Certified Great Place to Work with a people-first, collaborative culture.
• Access to 10+ cutting-edge technology practices and continuous learning opportunities.
• Competitive compensation, benefits, and a team that celebrates wins together.
• Flexible, remote-friendly work environment.