{"id":2152726,"url":"https://alion.io/job/generali-data-engineer-2","title":"Data Engineer","company":{"id":1773319,"name":"Generali","domain":"generali.com","url":"https://alion.io/company/generali-com","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Go Generali","truth_index":{"grade":"C","score":68,"open_postings":184,"ghost_share":0.533,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-13T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Milan, 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platforms and AI solutions architecture\nPromoting and managing the transition of the incumbent IT architecture to selected Cloud ecosystems\nEvaluating the architectural consistency of all the “digital touchpoints’’\nSupporting 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\nDefining, setting up and managing technology standards and solutions aimed mainly at calculation engines for analytics, Data Warehousing and Business Intelligence/Reporting tools; \nManaging the key Data Technology and Reporting Solutions taking care of their seamless operational functioning; \nTaking care of the development of data architectures functional to business needs, and of their implementation through state-of-the-art technologies and infrastructures \nManaging 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\nSteering 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\nThe selected candidate will:\nDesign, build, and maintain scalable data pipelines to support business analytics, machine learning models, and AI-driven decision-making.\nDevelop and optimize ETL processes, ensuring efficient data ingestion from multiple sources (structured and unstructured) into cloud-based data lakes and warehouses.\nImplement data quality frameworks and monitoring systems to ensure high data reliability, consistency, and governance.\nIntegrate machine learning workflows by developing feature stores, automating data preprocessing pipelines, and optimizing model training datasets.\nWork closely with MLOps teams to enable the deployment, monitoring, and lifecycle management of machine learning models in production.\nCollaborate with Cloud Data Platform engineers to optimize storage solutions, data processing frameworks, and cost-efficient cloud architectures.\nEnsure security and compliance with industry best practices and regulatory standards related to financial data.\nProvide technical leadership on emerging technologies, data engineering best practices, and scalable AI integration strategies.\nCoordinate withexternal resources on developing complex solutions in the data and machine learning domains\nOur ideal candidate will meet the following requirements:\n3+ years of experience in Data Engineering or Machine Learning Engineering\nStrong proficiency in Python (Pandas or similar, PySpark), SQL, or Scala for data manipulation and transformation\nExperience with cloud platforms such as AWS, Azure, or Google Cloud and data storage technologies (Redshift, DynamoDB, BigQuery, etc.)\nHands-on experience with distributed computing frameworks (Spark, Ray, etc.)\nSolid understanding of data modeling, data contracts, and governance frameworks\nExperience with MLOps tools and frameworks such as MLflow, Kubeflow, and Vertex AI\nFamiliarity with machine learning model operationalization and feature engineering\nBachelor’s degree in Computer Science, Engineering, or a related field\nNice to have:\nMaster’s degree or PhD in Data Science, AI, or a related field\nExperience in the financial or asset management sector\nFamiliarity with BI tools such as Power BI, Tableau, or Looker\nUnderstanding of regulatory requirements in financial data governance\nMain expected skills:\nExcellent communication and leadership skills\nPragmatic engineering approach to solve problems\nCollaborative mindset with a focus on driving business value through data\nStrong problem-solving abilities and capacity for abstraction\nAbility to manage multiple projects and deadlines in a fast-paced environment\nAbility to develop knowledge in new technologies and good proactivity\nGenerali Asset Management","description_format":"text","description_chars":4382,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Spa & Massage"],"lifecycle":[{"event":"open","at":"2026-10-09T05:51:20Z"}],"visa":[],"liveness":{"score":2,"band":"cold","label":"Long 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