Principal Business Intelligence Manager (Data Architecture)

TL;DR

Principal Business Intelligence Manager (Data Architecture): Defining the technical and data-product direction for hirify.global's customer experience data foundation with an accent on architecture, semantic-layer strategy, and scalable data-product patterns. Focus on designing governed, AI-ready data foundations and leading cross-organizational initiatives to ensure trustworthy, reusable metrics across the enterprise.

Location: Must be based in the United States

Salary: $136,400 – $229,400 annually (location-dependent)

Company

hirify.global is a leading real estate platform in the U.S. dedicated to helping customers navigate buying, selling, financing, and renting homes.

What you will do

• Define the target-state architecture for the customer experience data foundation, including taxonomy, identity resolution, and semantic logic.
• Design reusable semantic-layer and metrics-as-code patterns to ensure consistency across BI, analytics, and AI workflows.
• Drive alignment on metric definitions and data-product certification across product, finance, sales, and operations teams.
• Lead cross-organizational data initiatives, including build-versus-buy recommendations for analytics tooling and governance systems.
• Partner with Data Engineering and platform teams to ensure business architecture standards are implemented in production pipelines.
• Mentor senior BI managers and analytics engineers to shape technical standards and strategic direction.

Requirements

• Must be based in the United States
• 10+ years of experience in data architecture, enterprise data modeling, or BI data-product leadership.
• Expert-level SQL and data modeling skills with experience spanning multiple business domains.
• Deep expertise in semantic-layer design, metrics-as-code, and organizational-scale data governance.
• Strong understanding of how AI systems and machine-learning workflows consume structured, governed data.
• Proven ability to influence cross-functional stakeholders and gain alignment on complex data strategies.

Nice to have

• Experience in customer experience, operations, or marketplace data domains.
• Familiarity with Databricks, dbt, Snowflake, or similar analytics-engineering tooling.
• Experience reconciling competing sources of truth across workforce or operational systems.
• Background in preparing data foundations for AI and self-service analytics.

Culture & Benefits

• Competitive base salary and equity awards.
• Recognized as a Fortune 100 Best Company to Work For.
• Commitment to an inclusive, innovative, and engaging work culture.
• Support for professional growth and career development.
• Equal opportunity employer with a focus on diversity and inclusion.