Full Stack Software Engineer – Insight Analytics

🔥 1 minute ago

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Logo of CCT

CCT

51 - 200 employees

🏨 Hospitality

🍽️ Food & Beverage

📦 Logistics

Hospitality • Food & Beverage • Logistics

CCT is a B2B software company that provides Casino Insight, a cloud platform built exclusively for casinos to automate cash management, revenue audits, cage operations, and property-wide analytics. Their solutions replace manual, paper-based processes with unified data, automated workflows, and near-real-time insights across gaming, hotel, F&B, and retail operations, helping casinos reduce risk, improve efficiency, and increase profitability. CCT supports deployment and ongoing customer success, delivering measurable ROI and operational savings for casino operators.

📋 Description

• 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). • Bonus: Familiarity with Cube.dev or comparable semantic layers (dbt + a serving layer, LookML, AtScale, etc.). • Bonus: Experience with Embeddable or comparable embedded analytics frameworks. • Bonus: 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. • Bonus: Experience with serverless architectures and event-driven systems on AWS. • Bonus: Background working with data pipelines, warehouses (Iceberg, Snowflake, Redshift, etc.), or pre-aggregation strategies.

🏖️ Benefits

• Spec-driven development backed by AI tooling - we plan deliberately, then move fast. • Small team, high ownership, low ceremony. Engineers carry features end-to-end, weigh in on architecture and product decisions, and contribute to each other's reviews. Even as we grow, we expect that to stay true: more hands on the work, but the same expectation that you own what you ship. • AI tooling is part of how we build. We're investing in it deliberately and continuously, not as a novelty. • We care about getting the architecture right for the long haul, and we'd rather take a beat to plan than rebuild later.

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