Full Stack Software Engineer – Insight Analytics
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Job Description
Full Stack Engineer shipping a next-generation analytics product for gaming and hospitality industry. Building unified reporting and insights platform in a small, senior team.
Responsibilities:
- Design and ship full-stack features across our TypeScript frontend and TypeScript Lambda backends.
- Model data and metrics in Cube.dev; build embedded analytics experiences using Embeddable components.
- Own the production lifecycle of your features: CI/CD, performance, observability, and post-deploy validation.
- Implement your own AWS infrastructure (Lambda, IAM, networking, storage) using Terraform; we have a dedicated AWS engineer who will review and partner with you on the harder pieces.
- Work day-to-day in Claude Code and contribute to the team's AI context library, prompts, and process improvements.
- Pair with our designer, data engineers, and dashboard configuration lead to land features that hold up against real customer data.
Requirements:
- 3–5 years of professional software engineering experience shipping production systems.
- Strong working knowledge of TypeScript across frontend (React) and backend (Node/Lambda or similar).
- Familiarity with Python. We don't write a ton of it in this role, but enough that you should be comfortable reading and contributing where it shows up.
- Real experience using Claude Code or comparable agentic coding tools as part of your daily workflow.
- Hands-on experience with AWS in a production environment.
- **Bonus**
- Experience building analytics or BI products (dashboards, drill-down, semantic modeling, query performance).
- Familiarity with Cube.dev or comparable semantic layers (dbt + a serving layer, LookML, AtScale, etc.).
- Experience with Embeddable or comparable embedded analytics frameworks.
- Terraform or other IaC. You don't need to be the AWS expert on the team, but if you can spin up your own infrastructure and bring it for review, that's a strong plus.
- Experience with serverless architectures and event-driven systems on AWS.
- Background working with data pipelines, warehouses (Iceberg, Snowflake, Redshift, etc.), or pre-aggregation strategies.
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