Tech Lead - Data & AI
Pubblicato il 31-07-2026 - Altro in Milano
Experteer Overview
Se desidera saperne di più su questa possibilità o sta pensando di candidarsi, la preghiamo di leggere le seguenti informazioni.
In this role you will lead the data and AI engineering efforts to design and operate Generali Investments Holding’s cloud data platform. You will guide a small multidisciplinary team and collaborate with Group and local functions to embed data and GenAI solutions in a regulated financial environment. You will shape end-to-end data pipelines, data models, governance, and performance with a strong focus on scalable, enterprise-grade technologies. This is an opportunity to influence data strategy and drive innovation at scale.
Retribuzione / Benefits
Design and implement end-to-end data pipelines for ingestion, transformation, exposure, and visualization
Develop and evolve data models to support analytics and reporting
Implement data quality controls and governance policies
Maintain and optimize the Cloud Data Platform, monitoring KPIs, security, performance and costs
Troubleshoot data pipelines and platform issues with root‑cause analysis
Lead and mentor a small engineering team aligning with project requirements and standards
Define and implement GenAI and LLM‑based architectures (RAG, Agents)
Establish and enforce a coherent Data & AI governance framework
Collaborate with data analysts, data scientists, and business stakeholders to translate requirements into solutions
Promote a data-driven culture through cross-department collaboration
Responsabilità
5+ years as Data Engineer, Software Engineer, ML Engineer, or DevOps Engineer
1+ year in technical leadership or guiding small teams
Bachelor/Master's degree in Engineering, Computer science, or related field
Strong programming experience with Python and/or Node.js
Experience with DevOps and CI/CD tools (Git, xlwpduy GitHub, GitLab) and modern code assistants (GitHub Copilot, Claude Code)
Hands‑on experience with cloud-based data platforms (AWS preferred)
Strong SQL, NoSQL, and data modeling knowledge
Experience designing RESTful APIs
Familiarity with microservices, containers, and orchestration (Docker, Kubernetes - ECS, Fargate, EKS)
Knowledge of data quality, data governance, and monitoring practices
Experience with data technologies such as Spark, Pandas, Polars, Airflow
Strong understanding of LLM architectures, including RAG and agent‑based systems
#J-18808-Ljbffr