Senior Data & AI Solutions Architect - Pre-Sales (Retail)

Databricks; Seattle (WA); On-site; USD 219,000 - 301,000; Full time

Job summary

Databricks is seeking experienced pre-sales professionals to lead the technical strategy for Retail SA accounts, driving data-driven transformation and ML/AI adoption across large enterprise customers.

You will collaborate with Account Executives and cross-functional teams to build proofs of concept and guide customers through Databricks solutions, with an emphasis on data strategies and successful deployments.

Qualifications

• 6+ years in Retail/CPG with large (> $1m ARR) accounts.
• 4+ years in pre-sales or sales support.
• Technical in big data, data science and cloud.
• 3+ years design/implementation in Hadoop, NoSQL, MPP, OLTP, OLAP or full data science lifecycle.
• 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.

Responsibilities

• You will work with up to 9 clients as the main technical voice for Databricks.
• Lead customers on a transformational journey, helping them 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.
• Align technical strategies around Databricks solutions.
• Provide structured mentorship for other team members.

Skills

Pre-sales experience

Data-driven transformation

Big data knowledge

Cloud technologies

Python

R

Scala

Java

Databricks knowledge

Tools

Hadoop

NoSQL

MPP

OLTP/OLAP

Job description

Databricks is seeking experienced pre-sales professionals to lead the technical strategy for Retail SA accounts, driving data-driven transformation and ML/AI adoption across large enterprise customers.

You will collaborate with Account Executives and cross-functional teams to build proofs of concept and guide customers through Databricks solutions, with an emphasis on data strategies and successful deployments.