Data Engineer

Atlante Srl; Turbigo; Sur place; EUR 70 000 - 110 000; Plein temps

Résumé du poste

Atlante Srl is seeking a Data Engineer to join the Data Platform & AI team. You will review Atlante’s data architecture end-to-end, lead its redesign and treat AI agents as first-class users of the platform.

You will design the architecture that lets AI systems work on our data, define company-wide data standards, and build reliable data pipelines on a lakehouse, with governance, documentation and observability at the core.

Qualifications

• Experience designing and implementing data architectures for scalable platforms.
• Strong understanding of data governance and semantic consistency.
• Experience working with AI agents or AI-powered data workflows is a plus.

Responsabilités

• Review current data architecture and data platform end to end, map weaknesses and technical debt, and define target architecture and roadmap.
• Design and build the agentic harness architecture for AI agents to access, understand and act on Atlante’s data with clear permissions, evaluation and observability.
• Build and own the semantic layer, ensuring shared business definitions and metrics across BI, analytics and AI agents.
• Set up the knowledge management architecture that connects documentation, data catalog and business glossary to AI systems.
• Design, develop and operate reliable data pipelines on our lakehouse (Spark, SQL, Trino, Athena), with testing, data quality and monitoring built in.
• Apply data product management, defining data products with clear owners, contracts, service levels and consumers.
• Promote agentic development as the default way of building (coding agents, spec-driven development) with review practices to keep output production-grade.
• Define and spread data engineering standards across Atlante, including modeling conventions, CI/CD, documentation, access management and data governance.
• Stay abreast of the latest technologies in data and AI, testing them hands-on and bringing into the platform those that deliver real value.

Connaissances

Data engineering

Data pipelines

Data modeling

CI/CD

Outils

Spark

SQL

Trino

Athena

Description du poste

What if you could redesign how an entire company turns information into decisions, for people and AI agents alike?

We are looking for a Data Enginer to join our Data Platform & AI team!

Brief description of the role:

You 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.

Value creation:

You 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.

Core Responsibilities:

• Review 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.
• Design 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.
• Build and own the semantic layer, ensuring shared business definitions and metrics across BI, analytics and AI agents.
• Set up the knowledge management architecture that connects documentation, data catalog and business glossary to AI systems, including through MCP.
• Design, develop and operate reliable data pipelines on our lakehouse (Spark, SQL, Trino, Athena), with testing, data quality and monitoring built in from the start.
• Apply data product management, defining data products with clear owners, contracts, service levels and consumers.
• Promote 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.
• Define and spread data engineering standards across Atlante, including modeling conventions, CI/CD, documentation, access management and data governance.
• Stay abreast of the latest technologies in data and AI, testing them hands‑on and bringing into the platform those that deliver real value.