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

job descriptionWe 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 tasksFullstack Product Engineering: Build backend services, APIs, internal tools, lightweight UI/admin screens, automation, job runners, integrations, and customer-specific configuration around the dataData 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 inconsistenciesCurated Data Products: Create validated, analysis-ready datasets with consistent schemas, reproducible transformations, and clear naming for reporting, APIs, product features, and customer-facing analyticsCloud & Production Ownership: Deploy and operate reliable cloud solutions, preferably AWS, owning monitoring, alerts, failure handling, performance, cost, and operational reliabilityyour profileAI-Native DevelopmentHands-on with Claude Code, Codex, and agent-based workflows; GitHub Copilot-style autocomplete alone is not enoughFamiliar with worktrees, subagents, MCP, structured prompts, harness engineering, parallelization, and validating AI-generated code and analysis to production qualitySoftware EngineeringStrong fullstack/backend experience, ideally with Python and/or TypeScriptAble to build production-grade services, APIs, scripts, tools, automation, and clean interfaces; comfortable with version control, review, debugging, testing, and existing systemsData Engineering & AnalyticsStrong SQL, data modeling, analytical schemas, transformations, and downstream data useAble to translate product-defined KPIs into datasets and metrics, and validate messy operational data, edge cases, system limitations, and customer-specific differencesCloud & InfrastructureHands-on with AWS or similar cloud environments, including storage, databases, queues, containers, serverless/scheduled processing, SDKs, and APIsUnderstands deployment, secrets, networking, permissions, runtime configuration, scalability, performance, cost, and operational trade-offsGood 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 benefitsCollaboration in an empathetic, appreciative team with room to contribute ideas and take ownershipIndividual development opportunities, structured onboarding, and interdisciplinary collaborationFlexible working models including hybrid work, home office, and mobile workingA modern tech environment and agile ways of workingAdditional benefits such as pension plans, health offers, and employee discountsi look forward to receiving your applicationSvenja KrüßelD-49835 Wietmarschen-LohneTel.: 0170-7888740E-Mail: zvoove.com">career@zvoove.comOriginally posted on Himalayas