Databricks Solution Architect

🕒 August 5

🇨🇦 Canada – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bits In Glass

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2002

💼 Consulting

📦 Logistics

🏭 Manufacturing

💰 Private equity on 2024-03

Consulting • Logistics • Manufacturing

Bits In Glass is a global boutique consulting firm that designs, builds, and manages intelligent automation and integration solutions for enterprise clients. The company specializes in enterprise AI and data engineering, low-code/no-code development, process automation (including RPA and BPA), enterprise application integration, CRM implementations, and application management services, working with partners like Appian, AWS, UiPath, MuleSoft, Snowflake, and Creatio. Bits In Glass serves industries such as banking and financial services, insurance, transportation and logistics, manufacturing and distribution, real estate, healthcare, and the public sector, helping organizations scale automation, improve efficiency, and turn data into actionable insights.

📋 Description

• Design scalable Databricks solution architectures using Lakehouse, Delta Lake, and Unity Catalog patterns tailored to customer environments and business goals • Lead technical discovery workshops covering customer objectives, data challenges, and current-state architecture • Build working prototypes, proofs-of-concept, and reference architectures for the Databricks Lakehouse Platform • Guide customers on data pipelines, data modeling, and platform governance best practices • Advise on integrating Databricks with AWS, Azure, GCP, and adjacent data tooling • Demonstrate Databricks capabilities across Data Engineering, Data Science, ML, and Generative AI use cases • Identify and mitigate technical risks early to prepare delivery teams for success • Translate complex technical concepts into business value for technical stakeholders and executives • Partner with account teams throughout the sales process to shape technical strategies • Collaborate with Data Scientists and ML Engineers on AI-powered demo assets and reference architectures • Serve as a Databricks expert within BIG and enable the broader team • Contribute reusable accelerators, demo assets, and technical playbooks • Stay current on Databricks 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

🎯 Requirements

• 3+ years of hands-on experience with Databricks and/or Snowflake in a technical capacity • 5+ years in customer-facing technical roles such as solutions architecture, technical consulting, or sales engineering • Experience designing, presenting, and delivering production data architectures for enterprise customers • Experience with 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 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 • Exceptional verbal and written communication and presentation skills • Ability to 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 • Travel up to 15% for customer meetings and partner collaboration • Nice-to-have degree in Computer Science, Applied Mathematics, Operations Research, or a related quantitative field • Nice-to-have experience with dbt, Fivetran, Airflow, Delta Sharing, AI/GenAI frameworks, LLM application patterns, or Frontier LLMs such as Claude code • Nice-to-have Databricks GenAI Engineer Associate certification • Nice-to-have exposure to enterprise engagement cycles and technical deal outcomes

🏖️ Benefits

• Work on meaningful, high-impact data and AI projects for enterprise clients across Canada, the US, UK, and India • 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 • Team that celebrates wins together • Flexible, remote-friendly work environment