Life Sciences Field Engineering Lead

Neon

United States

On-site

USD 197,000 - 271,000

Full time

14 days+

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Job summary

Databricks is seeking a Manager, Specialist Solutions Architect to lead a team of specialists within the Life Science vertical, guiding pre-sales and delivery teams to drive technical wins and accelerate cloud consumption.

You will collaborate with cross-functional teams to strategize, scale the group, and promote data-driven AI solutions across healthcare contexts, including genomics, clinical trials, and real-world evidence.

Qualifications

  • Leadership experience building and guiding teams in a high-growth environment.
  • Deep design/implementation expertise in large-scale life sciences data solutions.
  • Strong knowledge of HIPAA, GDPR, HL7, FHIR, and DICOM standards.
  • Experience with genomics, bioinformatics, clinical trials, and real-world evidence.
  • Background in data engineering, databases, or data science.
  • Experience in senior pre-sales or post-sales roles for big data/cloud/SaaS.

Responsibilities

  • Hire and scale the Specialist Solutions Architect team for the Life Sciences vertical.
  • Foster a collaborative culture within a hyper-growth team while upholding Databricks values.
  • Drive product adoption and accelerate use cases to production in Life Sciences.
  • Collaborate with Sales, Marketing, Support, Product, and Operations to align goals and drive consumption targets.

Skills

Leadership experience
Life sciences domain knowledge
Regulatory knowledge (HIPAA/GDPR)
HL7/FHIR/DICOM familiarity
Pre-sales / post-sales experience
People management
Data-driven decisions
AI and cloud software models
Process optimization

Education

Bachelor's Degree in STEM
Master's degree (MSc) desirable

Job description

Databricks is seeking a Manager, Specialist Solutions Architect to lead a team of specialists within the Life Science vertical, guiding pre-sales and delivery teams to drive technical wins and accelerate cloud consumption.

You will collaborate with cross-functional teams to strategize, scale the group, and promote data-driven AI solutions across healthcare contexts, including genomics, clinical trials, and real-world evidence.

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