Databricks
Solutions Architect - Retail
$180K–$248K
Chicago, Illinois +8 · Remote · Full-time · Posted Oct 29, 2026
- Location
- Chicago, Illinois
Florida
Northeast - United States
Remote - Georgia
Remote - Massachusetts
Remote - New York
Southeast - United States
Tennessee
Florida - Experience
- 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
- Education
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience).
About the job
Leads customer technical strategy and designs production-grade data and AI architectures to drive Databricks adoption and growth.
What you'll do
- Own account technical strategy from discovery through production deployment and increased consumption.
- Lead architecture discussions and design scalable solutions across data engineering, ML/AI, and real-time analytics.
- Advise customer technical leaders, coordinate cross-functional resources, and provide structured feedback to influence product direction.
What they ask for
- Strong Python and SQL coding proficiency, including live coding, debugging, and solution building.
- Deep expertise in distributed data systems, including scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Experience deploying production solutions on AWS, Azure, or GCP, including infrastructure, security, and governance.
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience).
Nice to have
- Databricks certifications (Data Engineer, ML, Platform).
- Experience with competitive platforms such as Snowflake, AWS native services, or Azure Synapse.
Pay
$180,000 — $247,500 USD (total pay range for a commissionable role or expected salary range for a non-commissionable role; posting does not specify which applies).
Tools
Python, SQL, Databricks Platform, AWS, Azure, GCP, Snowflake, Azure Synapse
AI focus
Designs solutions spanning ML/AI and supports customers’ data and AI strategies; develops a technical specialization that may include ML/AI.
Model-written summary · the original posting is authoritative