Sr. Solutions Engineer - MFG
AI summary of the role
Databricks seeks a Sr. Solutions Engineer to drive technical strategy for large enterprise accounts in the Northeast US, focusing on adoption of ML & AI.
What you’ll do
- Act as the main technical voice for Databricks across multiple clients
- Lead customers on a transformational journey to evaluate and adopt Databricks
- Implement the technical strategy in the account in close alignment with the overall strategy
- Build a movement of technical champions within the account
What you’ll bring
- Proficiency at establishing and leading virtual teams to success within accounts
- Experience working very large (> $1m ARR), global accounts
- Ability to form relationships with executives and influencers
- Technical expertise in big data, data science, and cloud (Azure & AWS)
Technologies
Databricks · Apache Spark · Delta Lake · MLflow · Azure · AWS · Python · R · Scala · Java
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: Northeast, US REQ ID - FEQ327R20 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:
More from the job description
Location: Northeast, US REQ ID - FEQ327R20 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 [... source excerpt omitted ...] 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(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 j
Employer postings · Data from · Sources