Databricks PreSales Engineer

Bits In Glass•Canada Remote, ON

4d•Remote

About The Position

Bits In Glass (BIG) is a high-growth AI and automation consulting firm with offices across Canada, the United States, India, and the United Kingdom. Our portfolio spans more than 10 leading technologies across AI, cloud, data, automation, and business applications. Recognized globally as a Great Place to Work and the recipient of multiple partner excellence awards, BIG is built on collaboration, innovation, and delivering measurable business outcomes for enterprise clients. We are a team of experienced technology professionals who enjoy solving complex challenges, celebrating wins together, and helping customers modernize with confidence. BIG is looking for a highly motivated Databricks Pre-Sales Engineer to join our growing team. In this role, you will serve as the technical bridge between our sales organization and prospective customers, combining deep Databricks expertise with strong business acumen to design compelling data and AI solutions. You will own the technical side of the sales cycle — from discovery and architecture design to solution demonstrations and proof-of-concept (POC) delivery. This role is ideal for someone who enjoys customer engagement, solution storytelling, hands-on engineering, and helping organizations unlock value from modern data and AI platforms.

Requirements

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.
Proven ability to translate business requirements into technical solutions and gain 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 Haves

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.
Background in enterprise sales cycles and deal structuring.
DBX GenAI Engineer Associate certification

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.