PpThe Data Technologies, Analytics and BI Solutions team is responsible for: /p ul liDefining and setting up advanced technological solutions, strategies and standards to manage the overall Company data, to constantly improve automated data exchange within the IT platforms and AI solutions architecture /li liPromoting and managing the transition of the incumbent IT architecture to selected Cloud ecosystems /li liEvaluating the architectural consistency of all the “digital touchpoints’’ /li liSupporting in developing new business/organizational models based on cloud digital platforms, to leverage big data analytics, machine learning capabilities and help the business grow/optimize costs /li liDefining, setting up and managing technology standards and solutions aimed mainly at calculation engines for analytics, Data Warehousing and Business Intelligence/Reporting tools; /li liManaging the key Data Technology and Reporting Solutions taking care of their seamless operational functioning; /li liTaking care of the development of data architectures functional to business needs, and of their implementation through state-of-the-art technologies and infrastructures /li liManaging requirements gathering and analysis, technical solution design and implementation, maintenance and evolution of related systems and of the other data technology and reporting solutions and their related technological and infrastructural framework /li liSteering and managing the relationship with the external IT vendors providing data technology and reporting solutions and services to the Company, overseeing the service levels delivered and the consistency of the solutions; proposed with the overall technology and systems framework of the Company /li /ul h3The selected candidate will /h3 ul liDesign, build, and maintain scalable data pipelinesto support business analytics, machine learning models, and AI-driven decision-making. /li liDevelop and optimize ETL processes, ensuring efficient data ingestion from multiple sources (structured and unstructured) into cloud-based data lakes and warehouses. /li liImplement data quality frameworks and monitoring systemsto ensure high data reliability, consistency, and governance. /li liIntegrate machine learning workflowsby developing feature stores, automating data preprocessing pipelines, and optimizing model training datasets. /li liWork closely with MLOps teamsto enable the deployment, monitoring, and lifecycle management of machine learning models in production. /li liCollaborate with Cloud Data Platform engineersto optimize storage solutions, data processing frameworks, and cost-efficient cloud architectures. /li liEnsure security and compliancewith industry best practices and regulatory standards related to financial data. /li liProvide technical leadershipon emerging technologies, data engineering best practices, and scalable AI integration strategies. /li liCoordinate with external resources on developing complex solutions in the data and machine learning domains /li /ul h3Requirements /h3 pOur ideal candidate will meet the following requirements: /p ul li3+ years of experience in Data Engineering or Machine Learning Engineering /li liStrong proficiency in Python (Pandas or similar, PySpark), SQL, or Scala for data manipulation and transformation /li liExperience with cloud platforms such as AWS, Azure, or Google Cloud and data storage technologies (Redshift, DynamoDB, BigQuery, etc.) /li liHands-on experience with distributed computing frameworks (Spark, Ray, etc.) /li liSolid understanding of data modeling, data contracts, and governance frameworks /li liExperience with MLOps tools and frameworks such as MLflow, Kubeflow, and Vertex AI /li liFamiliarity with machine learning model operationalization and feature engineering /li liBachelor’s degree in Computer Science, Engineering, or a related field /li /ul h3Nice to have /h3 ul liMaster’s degree or PhD in Data Science, AI, or a related field /li liExperience in the financial or asset management sector /li liFamiliarity with BI tools such as Power BI, Tableau, or Looker /li liUnderstanding of regulatory requirements in financial data governance /li liExcellent communication and leadership skills /li liPragmatic engineering approach to solve problems /li liCollaborative mindset with a focus on driving business value through data /li liStrong problem-solving abilities and capacity for abstraction /li liAbility to manage multiple projects and deadlines in a fast-paced environment /li liAbility to develop knowledge in new technologies and good proactivity /li /ul h3Company Profile /h3 pGenerali is a major player in the global insurance industry – a strategic and highly important sector for the growth, development and welfare of modern societies. Over almost 200 years, we have built a multinational Group that is present in more than 60 countries, with 470 companies and nearly 80,000 employees. Our Group aims to become the standard bearer and industry leader in the European retail insurance market, building on our existing base of 50 million retail clients, out of an overall total of 72 million. /p pGenerali Asset Management is a European investment specialist, offering a wide range of active funds and bespoke solutions across both public and private markets. Our investment experience is grounded in a solid heritage, with skills that have been developed and honed over time by managing Generali Group and external clients' assets. /p pGenerali Asset Management S.p.A. guarantees a solid framework of services designed to support various asset management activities. Key elements include the provisioning of IT services over all applications underpinning the investment and asset management value chain (Front Office, Trading Desk, Investment Compliance, Middle and Back Office, Analytics and Reporting, etc.). /p /p #J-18808-Ljbffr