Azure Data Engineer AI Pipelines
Posted
Summary
Designs, builds, and maintains production Azure data pipelines powering GEI's AI and digital initiatives, integrating enterprise sources and preparing governed data for AI/RAG consumption using Python, SQL, and Azure services like Data Factory, Synapse, and Data Lake Storage.
Build GEI’s AI data foundation with Python, SQL, and Azure services supporting reliable enterprise pipelines and integrations.
As a Data Engineer, you will design, build, and maintain production data pipelines for GEI’s AI solutions and digital initiatives. You will manage Azure data services, integrate enterprise sources, and prepare governed data for AI consumption. The work includes collaboration with AI Engineers, solution architects, and platform teams.
Key Responsibilities:
Design pipelines ingesting, transforming, and delivering enterprise data Develop integrations using APIs, Graph connectors, and event-driven architectures Maintain data stores and indexing for RAG patterns Implement quality, validation, lineage, and governance controls Instrument pipelines for monitoring, cost, and performance optimization Requirements:
Four-plus years building and operating production data pipelines Proficiency in Python and SQL Experience with Azure Data Factory, Synapse, Data Lake Storage, and Azure SQL Experience with structured, semi-structured, and unstructured data Knowledge of security, privacy, access control, and encryption Apply data engineering expertise across Azure, Python, SQL, governance, and AI retrieval infrastructure at GEI.
Design pipelines ingesting, transforming, and delivering enterprise data Develop integrations using APIs, Graph connectors, and event-driven architectures Maintain data stores and indexing for RAG patterns Implement quality, validation, lineage, and governance controls Instrument pipelines for monitoring, cost, and performance optimization Requirements:
Four-plus years building and operating production data pipelines Proficiency in Python and SQL Experience with Azure Data Factory, Synapse, Data Lake Storage, and Azure SQL Experience with structured, semi-structured, and unstructured data Knowledge of security, privacy, access control, and encryption Apply data engineering expertise across Azure, Python, SQL, governance, and AI retrieval infrastructure at GEI.