25 ott - Milano
Atlante
pWhat if you could redesign how an entire company turns information into decisions, for people and AI agents alike? /p pWe are looking for a Data Enginer to join our bData Platform AI /b team! /p h3Brief description of the role: /h3 pYou are the technical point of reference for data engineering within the Data AI team. You review Atlante’s data architecture and data platform end to end and lead their redesign, treating AI agents as first-class users and builders of the platform. You design the architecture that lets AI systems work on our data and knowledge, and you define the standards the whole company follows when it produces, models and consumes data. /p h3Value creation: /h3 pYou turn Atlante’s data platform into a foundation that people and AI agents can trust: governed, documented and semantically consistent. By making data discoverable and self-explanatory, you shorten the path from question to answer. You raise the engineering bar of the whole organization by setting how data is modeled, tested, shipped and owned. /p h3Core Responsibilities: /h3 ul liReview the current data architecture and data platform end to end, map weaknesses and technical debt, and define the target architecture and the roadmap to get there. /li liDesign and build the agentic harness architecture through which AI agents access,
understand and act on Atlante’s data and knowledge, with clear permissions, evaluation and observability. /li liBuild and own the semantic layer, ensuring shared business definitions and metrics across BI, analytics and AI agents. /li liSet up the knowledge management architecture that connects documentation, data catalog and business glossary to AI systems, including through MCP. /li liDesign, develop and operate reliable data pipelines on our lakehouse (Spark, SQL, Trino, Athena), with testing, data quality and monitoring built in from the start. /li liApply data product management, defining data products with clear owners, contracts, service levels and consumers. /li liPromote agentic development as the team’s default way of building (coding agents, spec-driven development), with the review practices that keep the output production-grade. /li liDefine and spread data engineering standards across Atlante, including modeling conventions, CI/CD, documentation, access management and data governance. /li liStay abreast of the latest technologies in data and AI, testing them hands-on and bringing into the platform those that deliver real value. /li /ul #J-18808-Ljbffr
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