Presales Engineer (Databricks)

Roles and Responsibilities

• Lead technical discovery workshops to understand customer business objectives, data challenges, and current-state architecture.
• Design and present scalable Databricks-based solution architectures tailored to customer environments and business goals.
• Build and deliver compelling demos, prototypes, and proofs-of-concept showcasing the capabilities of the Databricks Lakehouse Platform.
• Partner closely with Account Executives throughout the sales lifecycle to develop winning technical strategies.
• Respond to RFPs, RFIs, and security questionnaires with clear, accurate, and persuasive technical content.
• Translate complex technical concepts into business value for both technical stakeholders and executive audiences.
• Design scalable data architectures on Databricks, including Lakehouse, Delta Lake, and Unity Catalog patterns.
• Guide customers on best practices for data pipelines, data modeling, and platform governance.
• Advise on integration of Databricks with hyperscaler environments (AWS, Azure, GCP) and adjacent data tooling.
• Identify and mitigate technical risks early in the sales process to set delivery teams up for success.
• Demonstrate Databricks capabilities for Data Science, ML, and Generative AI use cases.
• Collaborate with Data Scientists and ML Engineers to develop AI-powered demo assets and reference architectures.
• Stay current on Databricks platform releases, including Mosaic AI, MLflow, and Feature Store.
• Serve as a resident Databricks expert within BIG — sharing knowledge and enabling the broader team.
• Contribute reusable demo assets, accelerators, and technical playbooks.
• Represent BIG at customer events, webinars, and Databricks partner activities.
• Provide field feedback to Databricks product and partner teams to influence the roadmap.

Required Qualifications

• 5+ years in a pre-sales, sales engineering, or technical consulting role with a customer-facing focus.
• 3+ years of hands-on experience with Databricks in a technical capacity.
• At least one 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 SQL and proficiency in Python, Scala, Java, or R.
• Prowess in translating business requirements into technical solutions and gaining stakeholder buy-in at all levels.
• Experience designing, presenting, and delivering production data architectures for enterprise customers.
• Working knowledge of cloud platforms: AWS, Azure, and/or GCP.
• Excellent written and verbal communication skills — you can make complex topics clear and compelling.

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.
• Familiarity with AI/GenAI frameworks and LLM application patterns.
• Background in enterprise sales cycles and deal structuring.
• DBX GenAI Engineer Associate certification.

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.