Remote: Senior Data & AI Solutions Architect (Retail & Travel)

The Neon Company
United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Compensation
$219,100 - $301,300
Working hours
Regular working hours
Job source

Tech stack

Java (Programming Language) Artificial Intelligence Big Data Cloud Computing Apache Hadoop Python (Programming Language) Online Analytical Processing NoSQL Online Transaction Processing Operational Databases Data Analytics Databricks

Job description

We are looking for experienced pre-sales professionals with a proven track record of helping large enterprises become more data-driven. Working with the Account Executive (AE), the Retail and CPG Sr. SA defines and directs the technical strategy for our largest and most 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 Retail and CPG space., * You will work with 1-5 clients as the main technical voice for Databricks

  • You will lead your customers on a transformational journey, helping them to evaluate and adopt Databricks as part of their strategy
  • You will implement the technical strategy in the account, with a close understanding of the strategy
  • Build a movement of technical champions within the account
  • Align technical strategies around Databricks solutions
  • You will provide structured mentorship for other team members

Requirements

  • 8+ years of experience working in very large (> $1m ARR), from the Retail and CPG-related space
  • 4+ years working in a pre-sales capacity or supporting sales activity
  • Technical in big data, data science, and cloud
  • An ability in data-driven business transformation and driving change with data
  • 4+ years of experience with design and implementation experience in big data technologies such as Hadoop, NoSQL, MPP, OLTP, and OLAP, or full lifecycle data science solutions
  • Maintain and extend production data systems to evolve with complex customer needs
  • Production programming experience in Python, R, Scala, or Java
  • Nice to have: Databricks Certification

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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. Local Pay Range$219,100-$301,300 USD, 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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