Solutions Architect - Communications, Media, Entertainment and Games
Databricks Mosaic · New Jersey · San Francisco, California
CHECKED 15H AGO
Infrastructureonsitesenior$180k–$248k
At a glance
Highlights
- Lead end-to-end technical strategy from discovery to production deployment.
- Design scalable solutions spanning data engineering, ML/AI and real-time analytics.
- Serve as trusted advisor shaping customers' data and AI strategy.
What they offer
- Annual performance bonus
- Equity
Ideal candidate
A strategic, hands-on architect who thrives advising senior stakeholders and turning complex business needs into production-grade data and AI solutions. You love owning technical strategy and growing customer impact in media and entertainment.
Requirements
- 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
- Strong coding proficiency in Python and SQL with live coding, debugging and solution-building skills
- Deep expertise in distributed data systems architecture including scalable pipelines, streaming and lakehouse patterns
- Proficient on the Databricks Platform with a developing technical specialization
- Proven ability to lead architecture discussions with senior technical stakeholders
- Experience with production deployments on public cloud including infrastructure, security and governance
- Track record of driving platform adoption and consumption growth within accounts
- Excellent communication skills translating complex architectures into business value
- Bachelor's or Master's degree in Computer Science, Engineering, or quantitative discipline or equivalent experience
- hiring process
- Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check
Lab profile
About Databricks Mosaic
Builds unified data analytics and AI platform to productionize AI applications.
What they build
- Databricks platform
- Unified Data Analytics and AI
- AI platform
Known for
- Forward-deployed AI engineering
- Productionizing first-of-kind AI applications
- Customer platform adoption and scale
- Cross-functional engineering and product collaboration