Senior Azure Data Architect for GenAI & RAG

Software Product Development Company; Colombia; Remote; COP 245,520,000 - 357,120,000; Full time

Benefits offered by this job

Remote work

Career development

Mentorship program

Company library access

Job summary

SPD Technology is seeking a Senior Azure Data Architect to design and own the data layer behind GenAI, RAG, and Agentic AI applications. You will ensure enterprise data is ingested, prepared, stored, governed, and readily available for AI consumption and retrieval.

You will work with Azure Data Platform technologies including Synapse, Databricks, SQL MI, Data Lake architecture, and Functions, shaping scalable, metadata-driven ingestion and data models across multiple workstreams.

Qualifications

• Experience designing data architectures for enterprise Azure environments.
• Hands-on data modeling and ingestion pipelines for GenAI/RAG/Agentic AI workloads.
• Proven ability to modernize data platforms and enable scalable data solutions.

Responsibilities

• Own and design the data architecture and data modeling for enterprise Azure environments.
• Design data layer supporting GenAI, RAG, and Agentic AI applications including ingestion, storage, and retrieval for AI consumption.
• Modernize existing data platforms with metadata/configuration-driven ingestion architectures.
• Work with structured and unstructured data across the enterprise platform.

Skills

Azure Data Platform

Azure Synapse Analytics

Azure Databricks

Azure SQL MI / SQL Server / T-SQL

Azure Data Lake / Lakehouse

Azure Functions

Tools

Azure Cosmos DB

Job description

SPD Technology is seeking a Senior Azure Data Architect to design and own the data layer behind GenAI, RAG, and Agentic AI applications. You will ensure enterprise data is ingested, prepared, stored, governed, and readily available for AI consumption and retrieval.

You will work with Azure Data Platform technologies including Synapse, Databricks, SQL MI, Data Lake architecture, and Functions, shaping scalable, metadata-driven ingestion and data models across multiple workstreams.