Senior Data Platform Solutions Engineer

WinsAbove

Northern (KY)

Hybrid

USD 152,000 - 209,000

Full time

8 days ago
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Job summary

Databricks is seeking a Sr. Solutions Engineer to independently lead technical engagements, owning discovery, design, and platform demonstrations. You will be a builder who codes, architects, and presents—linking technical depth with customer-facing skills to drive Databricks adoption.

You will manage frontline customer relationships and collaborate with the Account Executive to expand platform consumption across data engineering, analytics, and ML workloads.

Qualifications

  • 4+ years in data engineering, solutions architecture, technical pre-sales, or hands-on consulting.
  • Proficient in Python and SQL with production-quality code; live coding is an interview stage.
  • Experience designing data solutions on at least one public cloud (AWS/Azure/GCP).
  • Familiarity with distributed data systems (Spark/Delta Lake/Hadoop).
  • Experience leading technical customer conversations—discovery, whiteboarding, architecture reviews.

Responsibilities

  • Lead technical discovery and solution design for customer workloads across data engineering, analytics, and ML.
  • Build and deliver proofs-of-concept and live demos on the Databricks Platform to drive wins.
  • Own frontline technical relationships with customer engineers and data teams.
  • Develop account-level technical strategies with the Account Executive to grow platform usage.

Skills

Python
SQL
Public cloud

Education

Bachelor's or Master's in CS/Engineering/quantitative

Tools

Databricks Platform

Job description

Databricks is seeking a Sr. Solutions Engineer to independently lead technical engagements, owning discovery, design, and platform demonstrations. You will be a builder who codes, architects, and presents—linking technical depth with customer-facing skills to drive Databricks adoption.

You will manage frontline customer relationships and collaborate with the Account Executive to expand platform consumption across data engineering, analytics, and ML workloads.

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