Sr. Solutions Engineer
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Role details
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Job description
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
Requirements
Amazon Web Services (AWS), Apache Spark, Artificial Intelligence (AI), Big Data, Business Transformation, Cloud Computing, Data Analysis, Data Science, Diversity, Enterprise Sales, Equal Employment Opportunity (EEO), Executive Relationships, Facebook, Fortune 500 Customers, Java, LinkedIn, Microsoft Windows Azure, Pre-Sales, Process Improvement, Proof of Concept, Python Programming/Scripting Language, R Programming Language, Remote Team Management, Sales Management, Scala Programming Language, Team Player, Technical Leadership, Technical Sales, Technical Strategy, Use Cases, Value Selling
Benefits & conditions
Databricks is committed to fair and equitable compensation practices. The pay range(s) 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 anticipates 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. For more information regarding which range your location is in visit our page here.
Zone 2 Pay Range
$152,300-$209,450 USD
About Databricks, 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.
About the company
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.
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