Databricks Solution Architect
Bits In Glass • Remote-friendly (Canada)
About the Role
We are looking for a hands-on Databricks Solution Architect to design the data and AI platforms that power our enterprise clients. This is a deeply technical role for an architect who wants to stay close to the technology - shaping Lakehouse architectures, building working prototypes, and setting the technical direction that delivery teams carry forward.
You will work directly with prospects and customers to understand their data challenges and design solutions on the Databricks Lakehouse Platform that actually fit their environment. That means partnering with our account and delivery teams throughout the sales process, ensuring the architecture you propose gets built. This role is ideal for someone who enjoys solving hard data problems, solution storytelling, and being the trusted technical voice customers rely on.
What You'll Do
- 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.
Technical Leadership & Community
- 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.
What You Bring
- 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.
