31 lug - Cusano Milanino
Experteer Italy
Experteer Overview
In this role you drive data strategy and build scalable data assets and AI-powered workflows within the Growth & Marketing B2C Analytics team. You design the Data Mesh layer, create AI-driven data transformation workflows, and deliver dashboards that communicate insights to stakeholders. You collaborate across Marketing, Finance, Operations, and Product to optimize the consumer lifecycle and ROI, while owning the end-to-end testing pipeline. This is a hands‑on, impact-focused position in a fast-moving fintech environment.
Retribuzione / Benefits
- Lead design of Data Architecture and Data Mesh layer to align with federated data strategy
- Define and implement AI-powered agentic workflows for data transformation and exploration
- Build high-impact dashboards and reports using Hex or Looker
- Analyze complex datasets to identify patterns in Acquisition, Engagement, Retention, Monetisation
- Partner with Marketing, Finance, Operations, and Product to translate data insights into actions
- Own end-to-end testing pipeline from opportunity to experiment recommendations
Responsabilità
- 5+ years in data-related roles (Data Engineering, Analytics, BI)
- At least 3 years in high-volume or big data environments
- Strong command of SQL, dbt, and Python
- Experience with Git and notebook-based analytics (e.g., Jupyter) is a plus
- Hands‑on data modelling, ETL, data governance, and Data Mesh implementation at scale
- AI fluency: experience with AI tools, prompting, and agent interactions via APIs
- Analytical and problem‑solving skills with ability to work through ambiguity
- Stakeholder management and clear communication to translate technical findings into actionable recommendations
- Knowledge of Digital Consumer Lifecycle (Acquisition, Activation, Retention, Churn) and user economics (ARPU, CAC, LTV)
Requisiti fondamentali
- Private health insurance for you and family
- Stock Option Plan
- Relocation support
- Meal vouchers
- Professional development programs
- Hybrid working policy
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