Location: Ottawa, ON
As a Solutions Architect on the Canada team focused on Digital Native customers, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.
Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.
The impact you will have:
- You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
- Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
- Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
- Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.
What we look for:
- 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
- Experience building distributed data systems
- Comfortable programming in, and debugging, Python and SQL
- Have built solutions with public cloud providers such as AWS, Azure, or GCP
- Expertise in one of the following:
- Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
- Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
- Available to travel to customers in your region
- [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
- Nice to have: Databricks Certification
NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticpates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- 5+ years in data engineering, data science, technical architecture, or similar role
- Experience building distributed data systems
- Proficient in Python and SQL programming
- Experience with AWS, Azure, or GCP
- Expertise in Spark, Hadoop, Kafka, or similar data engineering technologies
- Expertise in pandas, scikit-learn, pytorch, Tensorflow, or similar data science technologies
- Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
- Databricks Certification
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
