Technical Product Owner - Lead Data AI Engineer

05 ago - Milano
Experteer Italy

Experteer OverviewAs Lead AI Data Engineer & Technical Product Owner, you design and scale data and AI capabilities that power enterprise AI, analytics, and Generative AI. You lead AI data engineering products, aligning with architecture, security, and governance to deliver trusted data assets. You own end-to-end data foundations—from ingestion to deployment and monitoring—while guiding agile delivery and cross-team collaboration. This role offers impact across business domains by accelerating AI product value and responsible innovation.

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Retribuzione / Benefits

Act as Technical Product Owner for AI Data Engineering products, platforms and capabilities
Translate business needs into scalable data and AI engineering solutions; define backlogs and roadmaps
Lead design and maintenance of scalable data pipelines for AI, analytics, ML, and Generative AI
Oversee batch, streaming and real-time data integration; ensure data quality and governance
Enable AI delivery with feature stores, vector databases, and model deployment pipelines
Collaborate with AI engineers and data scientists to operationalize AI solutions; establish MLOps and DataOps
Define cloud-native data platforms architecture patterns; ensure security,



compliance and cost efficiency
Lead Agile squads; drive DevOps, DataOps, and delivery governance
Ensure enterprise security, privacy, governance, and responsible AI compliance
Define and monitor OKRs/KPIs for platform adoption, data quality, and value realization
Responsabilità

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Engineering, Information Systems, Artificial Intelligence, or related disciplines
5-7+ years in Data Engineering, AI/Platform Engineering, or Cloud Data Platform roles
Proven experience designing enterprise-scale data pipelines and cloud-native platforms
Experience xlwpduy as Technical Product Owner, Delivery Lead, or Squad Lead
Expertise in ETL/ELT, Data Lakes, Lakehouse architectures, Data Warehousing, Metadata Management, and Data Governance
Hands‑on with Azure, AWS, or GCP; understanding Generative AI, LLMs, Vector Databases, RAG, AI agent architectures
Experience implementing MLOps, CI/CD, Infrastructure-as-Code, DataOps; strong SQL and Python; Agile/Scrum experience
Requisiti fondamentali

Annual premio based on performance
Vacation days
Parental leave (minimum 12 weeks)
Bereavement leave
Caregiver leave
Well‑being reimbursement

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