Solutions Architect - Manufacturing
AI summary of the role
Databricks seeks a Solutions Architect to drive technical strategy and adoption of its Data Intelligence Platform within large High Tech and Manufacturing accounts.
What you’ll do
- Work with multiple clients as the main technical voice for Databricks.
- Lead customers on a transformational journey to evaluate and adopt Databricks as part of their strategy.
- Implement the technical strategy in the account, in close understanding of the strategy.
- Build a movement of technical champions within the account.
What you’ll bring
- Proficiency at establishing virtual teams and leading them to success within the account.
- Experience working very large (> $1m ARR), global accounts.
- Form relationships with executives and influencers.
- Technical in big data, data science and cloud.
Technologies
Databricks · Apache Spark · Delta Lake · MLflow · Python · R · Scala · Java · ML · AI
About Databricks
Unified Data Intelligence Platform (lakehouse + Mosaic AI) used by 10,000+ orgs and 50%+ of the Fortune 500 for ETL, BI, ML, and GenAI.
Private Late
Source and classification
Technical pre-sales · Evidence for this classification:
Location: Chicago, IL | Minneapolis, MN While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in various cities around the Central US. Mission We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Enterprise Account Executive (AE), the Enterprise SA 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 solid 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
More from the job description
Location: Chicago, IL | Minneapolis, MN While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations in various cities around the Central US. Mission We are looking for experienced pre-sales professionals who have a successful track record helping large enterprises become more data-driven. Working with the Enterprise Account Executive (AE), the Enterprise SA 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 solid 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 High Tech and Manufacturing space Outcomes 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 o [... source excerpt omitted ...] n-makers that leads them down a path of success. Technical in big data, data science and cloud. 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 Certification Pay Range Transparency 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
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