Senior AI-Native Fullstack Engineer (m/f/d) - Data & Analytics

Planbition, a zvoove company, is building a modern analytics and Business Intelligence solution for the temp-staffing industry. They are seeking a product-minded fullstack engineer with a strong data focus to create reliable insights and analytical workflows from operational data.

Responsibilities:

• Build backend services, APIs, internal tools, lightweight UI/admin screens, automation, job runners, integrations, and customer-specific configuration around the data
• Ingest, validate, transform, and document ERP, API, SQL, file, and cloud data; map product-defined KPIs to available sources and identify gaps or inconsistencies
• Create validated, analysis-ready datasets with consistent schemas, reproducible transformations, and clear naming for reporting, APIs, product features, and customer-facing analytics
• Deploy and operate reliable cloud solutions, preferably AWS, owning monitoring, alerts, failure handling, performance, cost, and operational reliability

Requirements:

• Fullstack Product Engineering: Build backend services, APIs, internal tools, lightweight UI/admin screens, automation, job runners, integrations, and customer-specific configuration around the data
• Data Pipeline & Modeling: Ingest, validate, transform, and document ERP, API, SQL, file, and cloud data; map product-defined KPIs to available sources and identify gaps or inconsistencies
• Curated Data Products: Create validated, analysis-ready datasets with consistent schemas, reproducible transformations, and clear naming for reporting, APIs, product features, and customer-facing analytics
• Cloud & Production Ownership: Deploy and operate reliable cloud solutions, preferably AWS, owning monitoring, alerts, failure handling, performance, cost, and operational reliability
• AI-Native Development: Hands-on with Claude Code, Codex, and agent-based workflows; GitHub Copilot-style autocomplete alone is not enough
• Familiar with worktrees, subagents, MCP, structured prompts, harness engineering, parallelization, and validating AI-generated code and analysis to production quality
• Strong fullstack/backend experience, ideally with Python and/or TypeScript
• Able to build production-grade services, APIs, scripts, tools, automation, and clean interfaces; comfortable with version control, review, debugging, testing, and existing systems
• Strong SQL, data modeling, analytical schemas, transformations, and downstream data use
• Able to translate product-defined KPIs into datasets and metrics, and validate messy operational data, edge cases, system limitations, and customer-specific differences
• Hands-on with AWS or similar cloud environments, including storage, databases, queues, containers, serverless/scheduled processing, SDKs, and APIs
• Understands deployment, secrets, networking, permissions, runtime configuration, scalability, performance, cost, and operational trade-offs