Senior Solutions Engineer – Benelux, Data & AI Platform

Menlo Ventures

Amsterdam

Hybrid

EUR 120,000 - 160,000

Full time

7 days ago
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Job summary

Databricks is seeking a Senior Solutions Engineer to lead frontline technical engagements in the Benelux region. You will own discovery, solution design, and live demos, combining coding, architecture, and customer-facing skills to drive Databricks adoption.

You will build PoCs, manage relationships with customer engineers and data teams, and partner with Account Executives to expand platform usage across analytics, ML, and data engineering workloads.

Qualifications

  • Industry experience in data engineering, solutions architecture, or pre‑sales (prefer 3+ years).
  • Proficient in Python and SQL with production‑quality code. Live coding is part of interview.
  • Hands‑on data solutions design on at least one public cloud (AWS/Azure/GCP).
  • Experience leading technical customer conversations (discovery, architecture reviews).
  • Strong presentation and demo skills for live solutions.

Responsibilities

  • Lead discovery and design for customer workloads across data engineering, analytics, ML, and GenAI.
  • Build and deliver proofs‑of‑concept and live platform demos.
  • Own frontline technical relationships with customer engineers and data teams.
  • Develop technical strategies with the Account Executive to grow platform consumption.

Skills

Python
SQL
Live coding
Presentation skills
Customer engagements
Data engineering

Education

Bachelor's or Master's in Computer Science/Engineering/Data Science

Tools

Databricks Platform
Delta Lake
Apache Spark

Job description

Databricks is seeking a Senior Solutions Engineer to lead frontline technical engagements in the Benelux region. You will own discovery, solution design, and live demos, combining coding, architecture, and customer-facing skills to drive Databricks adoption.

You will build PoCs, manage relationships with customer engineers and data teams, and partner with Account Executives to expand platform usage across analytics, ML, and data engineering workloads.

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