Azure Data Platform Architect — AI, Data & Cloud Ops

AdventHealth; Florida; On-site; USD 110,000 - 150,000; Full time

Benefits offered by this job

Benefits from Day One (medical, dental

Paid Time Off from Day One

403-B Retirement Plan

Parental Leave

Career Development

Well-being Resources

Mental Health Resources

Pet Benefits

Job summary

AdventHealth in Florida is seeking a data engineer to design, implement, test, deploy, and support cloud-based data pipelines using Azure services and Snowflake. You will work with stakeholders to translate requirements into scalable, secure data products and support analytics across the organization.

The role emphasizes full lifecycle data management, AI capabilities adoption, and collaboration with data warehousing, BI, and analytics teams to improve data quality and platform automation.

Qualifications

• Proficiency with SQL.
• Understanding distributed computing with Spark, NiFi, Azure Data Factory and Snowflake.
• Experience managing CI/CD pipelines in Azure DevOps or GitHub.
• Experience with automation patterns in a Cloud DevOps model.
• Full stack design in Azure and Snowflake for production alignment.
• Knowledge of Big Data tools and data formats (Parquet/AVRO/ORC/CSV/JSON).

Responsibilities

• Designs, builds, tests, deploys, and maintains data pipelines on Azure Cloud.
• Leverages Azure Data Factory, Azure Functions, and Snowflake to deliver scalable data products.
• Implements security, governance, and data quality across the pipeline.
• Collaborates with BI, analytics, and product teams to satisfy data needs.
• Leads AI feature evaluation within Cloud Data Platform to improve productivity.

Skills

SQL Proficiency

Azure Data Factory

Azure Functions

Snowflake

CI/CD Pipelines

Cloud DevOps

Big Data

AI Capabilities

Data Engineering

Communication

Job description

AdventHealth in Florida is seeking a data engineer to design, implement, test, deploy, and support cloud-based data pipelines using Azure services and Snowflake. You will work with stakeholders to translate requirements into scalable, secure data products and support analytics across the organization.

The role emphasizes full lifecycle data management, AI capabilities adoption, and collaboration with data warehousing, BI, and analytics teams to improve data quality and platform automation.