Azure Data Engineer: Lakehouse & AI Pipelines

Zurich Insurance Company; Xico; On-site; MXN 600,000 - 1,200,000; Full time

Benefits offered by this job

Life Insurance

Major medical expenses insurance

Job summary

Zurich Insurance Company is seeking a data & AI architecture specialist in Mexico's Veracruz region to design scalable cloud data pipelines, build reusable data assets, and define enterprise-wide data blueprints. You will collaborate with analytics teams to enable self-service insights and oversee model deployment and monitoring.

The role emphasizes end-to-end data pipeline construction, vector stores, and ML/LLM deployment experience in a modern cloud environment.

Qualifications

• Experience with cloud-based data & AI platforms across Azure or AWS.
• Develop enterprise-grade data assets for analytics consumption.
• Experience with large-scale data ingestion, processing and storage architectures.

Responsibilities

• Design and build scalable data ingestion, storage, and real-time processing solutions in the cloud.
• Create enterprise-grade data assets for analytics consumption.
• Develop architectural blueprints for enterprise data and single source of truth systems.

Skills

Azure & AWS Cloud

Data & AI solutions

Azure services: Fabric, Databricks, DF

Cosmos DB

Document Intelligence

Cognitive Services

AI Foundry

Power Platform

Azure ML

Power BI

Copilot Studio

LLM deployments

Vector stores: Elastic

Vector stores: Pinecone

MongoDB Atlas

Redis

Snowflake

Redshift

Fabric (data warehouse)

TensorFlow

PyTorch

Scikit-Learn

Tools

Elastic

Pinecone

MongoDB Atlas

Redis

Job description

Zurich Insurance Company is seeking a data & AI architecture specialist in Mexico's Veracruz region to design scalable cloud data pipelines, build reusable data assets, and define enterprise-wide data blueprints. You will collaborate with analytics teams to enable self-service insights and oversee model deployment and monitoring.

The role emphasizes end-to-end data pipeline construction, vector stores, and ML/LLM deployment experience in a modern cloud environment.