Data Architect with Azure

Client

Our client is a leading global travel agency network specializing in luxury and experiential journeys. They are evolving their Analytics & Reporting capabilities to deliver clear, actionable insights that support informed decision‑making across products, programs, and leadership built on a scalable and efficient analytics foundation.

Position overview

We are seeking a Data Architect to define and evolve the foundational data structures that power internal reporting, partner analytics, and commercial insights. This role is responsible for canonical data modeling, identity linkage, attribution feasibility, and the overall Snowflake warehouse design. The Data Architect will ensure data can be reliably consumed by downstream analytics tools, including Tableau dashboards.

Responsibilities

• Design and maintain canonical data models across agency, advisor, partner, and transactional domains

• Define identity linkage strategies across multiple source systems and APIs

• Evaluate and document attribution feasibility for reporting and commercial analytics use cases

• Own Snowflake warehouse design, including facts, dimensions, and conformed entities

• Partner with Data Engineers to ensure architectural standards are implemented consistently

• Collaborate with BI and Tableau users to ensure data models support reporting and access needs

• Establish modeling standards, documentation, and data governance best practices

Requirements

• Experience with Snowflake, including analytical schema design and performance optimization

• Advanced experience with SQL for analytics and data modeling

• Experience working with Azure Blob Storage

• Experience with API‑driven ingestion patterns

• Strong knowledge of data warehousing concepts and analytics architecture

Nice to have

• Familiarity with DBT or similar transformation frameworks

• Experience with identity resolution or master data management

• General awareness of Tableau consumption patterns

• Understanding of Tableau Cloud, including how data models are consumed, filtered, and secured in dashboards