AI-Native Fullstack Engineer for Data Products

zvoove Group; Germany (OH); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Pension plans

Health offers

Employee discounts

Flexible working models

Job summary

zvoove Group is seeking a fullstack engineer with a strong data focus to drive AI-native analytics and data products across ERP data and KPIs. You will build backend services, data pipelines, and dashboards while embracing AI workflows and production-grade practices.

The role emphasizes hands-on with AI tools, data modeling, and cloud deployments (AWS), delivering reliable, customer-facing analytics and internal tooling.

Qualifications

• Strong fullstack/backend experience with Python and/or TypeScript.
• Experience building production-grade services, APIs, scripts, tools, automation, and data products.
• Strong SQL and data modeling skills for analytics datasets.

Responsibilities

• 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 KPIs to sources and identify gaps.
• Curated Data Products: Create validated, analysis-ready datasets with consistent schemas and reproducible transformations.
• Cloud & Production Ownership: Deploy and operate reliable cloud solutions, preferably AWS, with monitoring, alerts, and cost control.

Skills

Fullstack experience

Python

TypeScript

SQL

Data modeling

Analytical schemas

AI-native workflows

Harness engineering

Parallelization

Tools

Claude Code

Codex

Agent-based workflows

GitHub Copilot

Job description

zvoove Group is seeking a fullstack engineer with a strong data focus to drive AI-native analytics and data products across ERP data and KPIs. You will build backend services, data pipelines, and dashboards while embracing AI workflows and production-grade practices.

The role emphasizes hands-on with AI tools, data modeling, and cloud deployments (AWS), delivering reliable, customer-facing analytics and internal tooling.