Senior Data & AI Solutions Architect – Retail/CPG

Databricks

Charlotte (NC)

On-site

USD 219,000 - 301,000

Full time

14 days+
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Job summary

Databricks is seeking an experienced pre‑sales professional to partner with AEs and lead technical strategy for large Retail and CPG accounts. You will drive adoption of the Databricks platform, shape the technical roadmap, and nurture champions within customers to achieve data-driven transformation.

You will collaborate with hands-on resources, design PoCs, and articulate the value of ML and AI across use cases. 8+ years in data, cloud, and pre-sales preferred.

Qualifications

  • 8+ years in Retail/CPG pre-sales or equivalent.
  • Strong data and cloud technology background.
  • Experience with large ARR accounts >$1M.
  • Proven ability to drive data-driven transformation.
  • Experience with design/implementation in big data tech (Hadoop/NoSQL/MPP/OLTP/OLAP).
  • Production data systems maintenance and evolution.
  • Production programming in Python, R, Scala or Java.
  • Databricks Certification is a plus.

Responsibilities

  • You will be the main technical voice for 1–5 clients.
  • Lead customers on a transformational journey adopting Databricks as part of their strategy.
  • Implement the technical strategy within accounts and align with Databricks solutions.
  • Build a movement of technical champions within the account.
  • Provide mentorship for other team members.

Skills

Big data
Data science
Cloud
Python
R
Scala/Java
Databricks Certification

Tools

Hadoop
NoSQL
MPP
OLTP
OLAP
Python
Java

Job description

Databricks is seeking an experienced pre‑sales professional to partner with AEs and lead technical strategy for large Retail and CPG accounts. You will drive adoption of the Databricks platform, shape the technical roadmap, and nurture champions within customers to achieve data-driven transformation.

You will collaborate with hands-on resources, design PoCs, and articulate the value of ML and AI across use cases. 8+ years in data, cloud, and pre-sales preferred.

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