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

Zvoove; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Hybrid work model

Pension plans

Health offers

Employee discounts

Job summary

Zvoove is building a modern analytics and BI platform for the temp-staffing industry, integrating ERP data across countries into reliable, customer-facing insights and reusable data products. We seek a product-minded fullstack engineer with a strong data focus who uses AI-native workflows to move from messy data to validated datasets, pipelines, APIs, and dashboards.

You will own end-to-end development, including backend services, data pipelines, and internal tools, while ensuring correctness

Qualifications

• In-depth fullstack/backend experience with Python and/or TypeScript.
• Strong data engineering and analytics capabilities.
• Experience deploying cloud-based services (AWS or similar).
• Familiarity with AI-native workflows and validation of AI-generated code.

Responsibilities

• Fullstack Product Engineering: build backend services, APIs, internal tools, UI screens, and data integrations.
• Data Pipeline & Modeling: ingest, validate, transform ERP/API/SQL data; map KPIs to sources.
• Curated Data Products: create validated datasets with clear schemas for reporting and APIs.
• Cloud & Production Ownership: deploy and operate reliable cloud solutions with monitoring and cost control.

Skills

Fullstack engineering

Data focus

Python

TypeScript

SQL

Data modeling

AWS

AI-native development

Claude Code / Codex

Tools

GitHub Copilot

Job description

Job description

We are building a modern analytics and Business Intelligence solution for customers in the temp-staffing industry, integrating operational data from multiple ERP systems across countries into reliable, customer-facing insights, analytical workflows, and reusable data products.
This is not a traditional data analyst or classic BI developer role. We are looking for a product-minded fullstack engineer with a strong data focus: someone who can move from messy ERP data and product-defined KPIs to validated datasets, pipelines, APIs, internal tools, and dashboards where needed.
AI and LLM tooling are central to how we work. We expect someone who uses AI-native workflows to explore faster, build in parallel, validate assumptions, and ship high-quality production solutions.

What We’re Looking For

We are looking for a fullstack engineer with a strong data focus. You should turn ambiguous problems into working software, use AI as a default development workflow, care about correctness and maintainability, understand data edge cases, choose simple robust solutions, own the outcome from exploration to production, and move quickly while verifying aggressively.

Your tasks

• 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

Your profile

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

Software Engineering

• 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

Data Engineering & Analytics

• 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

Cloud & Infrastructure

• 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

Good Fit

You may be a good fit if you are a fullstack/backend engineer with strong data or analytics experience, a Python/TypeScript engineer who enjoys data products and automation, an analytics/data engineer with real software engineering depth, a technical founder/builder profile, or an AI-native engineer using LLMs and agents daily for production work.

Not a Good Fit

This role is probably not the right fit if you are mainly a dashboard-only BI analyst, classic report builder, pure data warehouse engineer waiting for predefined tickets, notebook-only analyst without production engineering experience, engineer with no interest in data modeling, someone who avoids ambiguity, or someone who does not actively use and rigorously validate AI-generated output.

Your benefits

• Collaboration in an empathetic, appreciative team with room to contribute ideas and take ownershipIndividual development opportunities, structured onboarding, and interdisciplinary collaboration
• Flexible working models including hybrid work, home office, and mobile working
• A modern tech environment and agile ways of working
• Additional benefits such as pension plans, health offers, and employee discounts

I look forward to receiving your application

Svenja Krüßel
D-49835 Wietmarschen-Lohne
Tel.: [phone]