Data Engineer

Summary

The Data Engineer is a member of the Data & AI team, accountable for building and maintaining scalable data pipelines, models, and semantic layers that power analytics, business intelligence, and AI-driven tools across the organization. This role supports structuring data for AI consumption, including developing models and semantic layers used by Microsoft Fabric Data Agents configured as MCP servers, while integrating and centralizing data from multiple sources. This role develops and optimizes data pipelines and workflows, ensures data is reliable and accessible, and partners with cross-functional stakeholders to deliver practical, data-driven solutions. The ideal candidate is strong in data modeling and engineering, with solid collaboration and problem-solving skills.

Data Modeling & Architecture

Design and build data models and semantic layers optimized for analytics, business intelligence, and AI use cases, including supporting Fabric Data Agents configured as MCP servers that expose curated, governed datasets to AI systems.

Design and manage dimensional data models (star/snowflake) within a medallion architecture to support business reporting, analytics, and AI use cases.

Support initiatives to centralize data from multiple systems into a single master dimensional model.

Ensure data structures and models support business intelligence tools and reporting needs, enabling data-driven decision-making across the organization.

Data Engineering & Automation

Develop and maintain efficient, scalable data pipelines for ingestion, transformation, and integration.

Automate workflows and data integration processes using Azure Data Factory, Microsoft Fabric, Logic Apps, APIs, and other relevant tools.

Pipeline & Dataflow Development

Continuously monitor and enhance data pipeline and data