Teams at Lingaro

Designs and oversees scalable data engineering architectures and implementations. The role translates business requirements into data solutions, guides engineering teams, ensures data quality and governance, optimizes performance, integrates systems, documents architecture, and supports project planning. It requires extensive Azure and Databricks expertise, proficiency in Python, PySpark, and SQL, knowledge of distributed computing and modern data platforms, and experience leading teams and working with stakeholders.

Build and productionize machine learning, generative AI, LLM, and automation solutions. Design industrialized processing pipelines, implement MLOps and LLMOps best practices, develop enterprise AI agents using Microsoft Copilot Studio and Azure AI Foundry, and integrate Microsoft and Azure services. Gather requirements, estimate work, present technical solutions, troubleshoot agents, and create documentation.

Design, build, and optimize GCP data ecosystems, including pipelines, data lakes, warehouses, storage architectures, and processing infrastructure. Gather requirements, model data, troubleshoot complex issues, tune performance, monitor systems, and support new functionality. Collaborate directly with clients and cross-functional teams, while mentoring junior data engineers and leading technical improvement discussions.