Bertoni Solutions

Data Engineer

• Design, build, and maintain scalable people-data models in the enterprise data warehouse
• Translate approved business and product requirements into technical data specifications, database designs, and reusable data assets
• Establish architecture patterns for dashboards, analytics products, scorecards, and approved AI use cases
• Partner with the Enterprise Data Team on source-data onboarding, engineering dependencies, release planning, and production implementation
• Maintain technical documentation for data models, integrations, transformation logic, dependencies, and platform components
• Identify and recommend architecture, platform, and infrastructure investments for an AI-ready People Data platform
• Establish automated data-quality monitoring, validation rules, reconciliation controls, and exception alerts
• Implement and maintain end-to-end data lineage
• Define and own production support, incident management, and escalation practices
• Monitor platform health, pipeline performance, refresh reliability, and recurring failure patterns
• Implement technical controls for access, privacy, confidentiality, retention, and sensitive-data handling
• Build and maintain the governed people-data foundation for approved AI, machine learning, and advanced analytics use cases
• Assess data readiness, reliability, representativeness, documentation, accessibility, and controls for AI use cases
• Support the People Data AI Control Tower and monitoring and traceability capabilities
• Own and execute the AI-readiness roadmap for the people data lake
• Serve as technical authority for the People Data platform infrastructure roadmap

People Data Engineer

• Build and maintain scalable people-data models within the enterprise data warehouse
• Translate approved business definitions and product requirements into technical data specifications, structures, and reusable data assets
• Establish architecture patterns for dashboards, analytics products, scorecards, and approved AI use cases
• Partner with the Enterprise Data Team on source-data onboarding, engineering dependencies, release planning, and production implementation
• Maintain technical documentation for data models, integrations, transformation logic, dependencies, and platform components
• Identify and recommend architecture, platform, and infrastructure investments for an AI-ready People Data platform
• Establish automated data-quality monitoring, validation rules, reconciliation controls, and exception alerts
• Implement and maintain end-to-end data lineage
• Define and own production support, incident management, and escalation practices
• Monitor platform health, pipeline performance, refresh reliability, and recurring failure patterns
• Implement technical controls for access, privacy, confidentiality, retention, and sensitive-data handling
• Partner with governance, privacy, legal, security, HR technology, and enterprise data stakeholders
• Build and maintain the governed data foundation for approved AI, machine learning, and advanced analytics use cases
• Support the technical design and implementation of the People Data AI Control Tower
• Own the AI-readiness roadmap for the people data lake and drive technical delivery
• Serve as the technical authority for the People Data platform infrastructure roadmap

• Design, build, and maintain scalable people-data models within the enterprise data warehouse
• Translate approved business and product requirements into technical data specifications, structures, and reusable data assets
• Establish architecture patterns for dashboards, analytics products, scorecards, and approved AI use cases
• Partner with the Enterprise Data Team on source-data onboarding, engineering dependencies, release planning, and production implementation
• Maintain technical documentation for data models, integrations, transformation logic, dependencies, and platform components
• Identify and recommend architecture, platform, and infrastructure investments for an AI-ready People Data platform
• Establish automated data-quality monitoring, validation rules, reconciliation controls, and exception alerts
• Implement and maintain end-to-end data lineage
• Define and own production support, incident management, and escalation practices
• Monitor platform health, pipeline performance, refresh reliability, and recurring failure patterns
• Implement technical controls for access, privacy, confidentiality, retention, and sensitive-data handling
• Partner with governance, Privacy, Legal, Security, HR Technology, and Enterprise Data stakeholders
• Build and maintain the governed data foundation for approved AI, machine learning, and advanced analytics use cases
• Assess data readiness, reliability, documentation, representation, accessibility, and controls for AI use cases
• Support the People Data AI Control Tower and monitoring and traceability capabilities
• Own the AI-readiness roadmap for the people data lake and drive execution of technical solutions
• Serve as technical authority for the People Data platform infrastructure roadmap