Within Data, AI Tech Solutions & IT Applications function in Generali Investments Holding, we are looking for a talented and proactive resource to join the team. As Tech lead – Data & AI, you will be responsible for development, maintenance, and enhancement of Generali Investments Holding’s cloud data architecture to ensure the integrity, efficiency, and accessibility of our data. You will guide a small multidisciplinary engineering team (Data & Software Engineers, Frontend Developer, DevOps Engineer) and collaborate closely with Group and local teams including Cloud, Security, and Data & AI functions. You will work with enterprise-grade technologies, define best practices across data engineering and software development, and play a key role in shaping next-generation Data & AI and GenAI solutions within a complex and regulated financial environment
Key Responsibilities:
- Design and develop end-to-end data pipelines for efficient and reliable data ingestion, transformation, exposure, and visualization, ensuring consistency and accuracy.
- Design, maintain and evolve data models to support analytical and reporting requirements.
- Implement data quality controls and monitoring processes to ensure the accuracy and reliability of data and contribute to the development and enforcement of data governance policies.
- Maintain and continuously improve the Cloud Data Platform, monitoring KPIs, security alerts, performance, and costs, and optimizing ETL processes.
- Troubleshoot and resolve data pipeline and platform issues, performing root-cause and cost/performance analyses.
- Lead and mentor a small engineering team, ensuring alignment with project requirements, timelines, and architectural standards.
- Define and implement GenAI and LLM-based architectures (e.g. RAG, Agents), integrating AI solutions into business processes effectively and safely.
- Establish and enforce a coherent Data & AI governance framework, balancing innovation, compliance, and risk management.
- Collaborate closely with data analysts, data scientists, and business stakeholders to translate requirements into robust technical solutions.
- Promote a data-driven culture through effective communication and cross-department collaboration.
Qualifications:
- 5+ years of experience as a Data Engineer, Software Engineer, ML Engineer, or DevOps Engineer.
- 1+ year of experience as a technical lead or in guiding small engineering teams.
- Bachelor/Master’s degree in Engineering, Computer science, or a related field.
- Strong programming experience with Python and/or Node.js.
- Solid experience with DevOps and CI/CD tools (e.g. Git, GitHub, GitLab) and modern code assistant tools (e.g. GitHub Copilot, Claude Code).
- Hands-on experience with cloud-based data platforms (AWS preferred).
- Strong knowledge of SQL, NoSQL databases and data modeling best practices.
- Experience designing and developing RESTful APIs.
- Familiarity with microservices architectures, containerization, and orchestration platforms (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.
Preferred Qualifications:
- Exposure to asset management or financial services industry.
Soft Skills:
- Excellent problem-solving and analytical skills.
- Ability to operate in a complex, regulated and evolving environment and guide teams through changing requirements.
- Proven capability as a technical mentor and leader.
- Strong communication and collaboration skills and team-oriented mindset.
- Fluency in English, both written and spoken