Databricks解决方案架构师
Databricks Solution Architect
Databricks 解决方案架构师
Bits In Glass • 远程办公友好（加拿大）
Bits In Glass（BIG）是一家高增长的AI和自动化咨询公司，在加拿大、美国、印度和英国均设有办公室。我们的产品组合涵盖AI、云、数据、自动化和业务应用领域的10多项领先技术。
作为全球认可的优秀工作场所，并多次获得合作伙伴卓越奖项，BIG以协作、创新和为企业的客户提供可衡量的业务成果为基础。我们是一支经验丰富的技术专业团队，享受解决复杂挑战、共同庆祝成功，并帮助客户有信心地进行现代化改造。
职位简介
我们正在寻找一位亲力亲为的Databricks解决方案架构师，为我们的企业客户设计数据和AI平台。这是一个高度技术性的角色，适合希望与技术保持紧密联系的架构师——塑造Lakehouse架构，构建工作原型，并设定交付团队继续推进的技术方向。
你将直接与潜在客户和客户合作，了解他们的数据挑战，并在Databricks Lakehouse平台上设计真正符合他们环境的解决方案。这意味着在整个销售过程中与我们的客户经理和交付团队合作，确保你提出的架构得以实现。这个职位适合喜欢解决复杂数据问题、进行解决方案叙事，并成为客户信赖的技术声音的人。
你将负责
- 设计可扩展的Databricks解决方案架构——包括Lakehouse、Delta Lake和Unity Catalog模式——根据每个客户的环境和业务目标进行定制。
- 主导技术发现研讨会，了解客户的业务目标、数据挑战和现有架构。
- 构建工作原型、概念验证和参考架构，展示Databricks Lakehouse平台的功能。
- 指导客户在数据流水线、数据建模和平台治理方面的最佳实践。
- 建议如何将Databricks集成到超大规模云环境（AWS、Azure、GCP）以及相关的数据工具中。
- 展示Databricks在数据工程、数据科学、机器学习和生成式AI用例中的功能，包括Mosaic AI、MLflow和特征存储。
- 早期识别并缓解技术风险，确保交付团队能够顺利推进。
- 将复杂的技术概念转化为易于理解的方案。
查看英文原文
Databricks Solution Architect
Bits In Glass • Remote-friendly (Canada)
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.
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.
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.
Originally posted on Himalayas