Product Engineer, EMEA
- Build demos, apps, and technical content that help customers see what's possible with Firebolt - and how to use it to deliver ultra-fast, scalable analytics.
- Help shape how we talk about Firebolt to developers and data engineers - translating technical features into real-world use cases that resonate.
- Partner with Product and Engineering to stay ahead of upcoming releases and ensure our documentation, demos, and messaging are ready to support them.
- Collaborate with Marketing and Sales to create assets that help users understand Firebolt's value and get started quickly - whether they're evaluating the product, using it in production, or building apps on top.
- Contribute to our presence in the data and developer ecosystem - by speaking at events, publishing technical content, or engaging with users in forums and Slack.
- Act as a voice for the developer - bringing feedback from the field into product discussions and helping Firebolt stay grounded in real-world needs.
- 5+ years in engineering, solutions engineering, solution architect roles.
- Proven experience building production-grade analytics systems, data pipelines, or data applications.
- Strong understanding of modern data infrastructure, with hands-on experience using cloud data warehouses and/or data lakes.
- Fluent in SQL, and comfortable with performance optimization and data modeling.
- Excellent written and verbal communication skills, with the ability to translate complex technical topics into engaging content.
- Experience creating developer-facing content such as technical blogs, demo apps, product tutorials, or internal enablement.
- Self-starter with strong project management skills and the ability to lead initiatives from concept to execution.
- Collaborative team player who enjoys working across disciplines and contributing to shared goals.
- Curious and connected - know what's happening in the industry, what users are building, and what tools they love (or hate).
- Prior experience working in startups or fast-paced product organizations.
- Background in AI, machine learning or dev tools.
- Experience speaking at industry conferences, running webinars, or building video tutorials.
- Contributions to open-source projects or active participation in developer/data communities.
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