Lead product software engineer
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We are looking for a Lead Product Software Engineer to drive the design, development and evolution of data-centric applications and platform services within Wolters Kluwer Italia. The role combines strong software engineering leadership with a deep understanding of data-intensive products, enabling analytics, benchmarking, reporting and reusable data services across multiple business domains. The person will actively contribute to implementation while setting technical direction, engineering standards and delivery practices. A key expectation is the adoption of modern AI-assisted software development practices, including specification-driven approaches such as Open Spec or equivalent methodologies, to improve quality, productivity, maintainability and clarity of delivery.
Key Responsibilities
Lead the design, development and technical evolution of data-centric applications and platform services. Define and maintain engineering standards, integration patterns, APIs and reusable technical capabilities. Design and implement ingestion, processing, storage, serving, monitoring and integration components supporting analytics and reporting use cases. Translate business and product needs into scalable, maintainable and secure technical solutions.
Contribute to the definition of data models, semantic layers and shared services supporting benchmarks, dashboards and data products. Leverage AI-assisted development practices to improve software quality, productivity, maintainability and engineering flow. Contribute to adoption of specification-driven engineering, including Open Spec or equivalent methodologies, as part of the software delivery lifecycle. Evaluate and incorporate emerging technologies, including AI-enabled capabilities, where they create measurable business value.
Ensure scalability, reliability, performance, security, observability and cost efficiency of implemented solutions. Mentor developers and contribute to a culture of engineering excellence, continuous learning and innovation.
Required Qualifications
Strong experience in software engineering, product development or platform engineering. Solid backend development experience, ideally in. NET-based environments. Experience designing and developing data-intensive applications, APIs, integrations or platform services. Good understanding of data ingestion, transformation, storage, serving and analytical consumption patterns. Experience using AI-assisted software development tools as part of the software delivery lifecycle.
Familiarity with specification-driven engineering approaches such as Open Spec or equivalent methodologies. Genuine interest in AI, software engineering innovation and cutting-edge technology. Ability to continuously evolve engineering practices through experimentation, automation and adoption of new tools and paradigms. Strong communication skills and ability to collaborate with Product, Engineering, Analytics and Business stakeholders. Additional Valuable Experience Experience with Microsoft Azure and cloud-native architectures.
Experience with Microsoft Fabric, Databricks, Synapse, Power BI or equivalent Data & Analytics technologies. Knowledge of Data Ops, observability, data governance, monitoring and cost optimization practices. Experience with large-scale data processing, benchmarking services or enterprise data products. Experience working in Agile, product-oriented and cross-functional environments.
What We Offer
We operate in a rapidly growing multinational environment and provide our teams with: People First: care and attention to the work environment, to people, and to their individual and professional growth within the Technology organization. Continuous Learning: Access to top-tier technological training platforms Access to high-quality learning paths through the internal #GROW program Knowledge-sharing communities Customized development paths International and Cross-functional Projects: opportunities to participate in international and cross-functional projects, ensuring the exchange of knowledge and ideas. Working Methodology: an operational approach based on a collaborative, informal work environment that is open to the exchange of ideas.
Benefits
Hybrid working model Flexible start and end times to support work-life balance Meal vouchers worth €8 Online well-being programs Welfare platform available to all employees
Location:
Milan and smart working #Li-Hybrid Our Interview Practices To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style.
We value authenticity