Location: Toronto, ON
REQ ID - FEQ327R207
We are looking for pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Enterprise Account Executive (AE), the Sr. Solutions Engineer defines and directs the technical strategy for our largest and important accounts, leading to more widespread use of our products and wider and deeper adoption of ML & AI. You will lean upon your background in value selling, technical account management and technical leadership to maximize success in these accounts. While you work with a team that includes hands-on resources who will build proofs of concept and demonstrate Databricks' products, you need to be technical and must understand the relevance and application of ML & AI within a range of use cases important to the target accounts in the greater region.
The impact you will have:
- You work with multiple clients as the main technical voice for Databricks.
- You lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
- You implement the technical strategy in the account, in close understanding of the strategy.
- You build a movement of technical champions within the account.
- You align technical strategies around Databricks solutions.
- You work with your sales team and technical peers to drive business outcomes for our clients
What we look for:
- Proficiency at establishing virtual teams, and leading them to ultimate success within the account.
- Experience working very large (> $1m ARR), global accounts.
- Form relationships with executives and influencers.
- Present a convincing point-of-view to important decision-makers that leads them down a path of success.
- Technical in big data, data science and cloud (Azure & AWS).
- An ability in data-driven business transformation, and driving change with data.
- Production programming experience in Python, R, Scala or Java
- Nice to have: Databricks, Snowflake, AWS or Azure Certification
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
- Proven pre-sales experience helping large enterprises become more data-driven
- Ability to lead virtual teams and implement technical strategy within accounts
- Experience working very large (> $1M ARR), global accounts
- Ability to form relationships with executives and present to decision-makers
- Technical expertise in big data, data science, and cloud (Azure and AWS)
- Production programming experience in Python, R, Scala or Java
- Experience in value selling, technical account management, and technical leadership
- Databricks, Snowflake, AWS or Azure 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.
