Staff Data Architect (AI)

Location: Remote across the Americas, including the US, Canada, Mexico, and LATAM. Hiring is stated to be across the US. Candidates must be authorized to work in the US or Canada.

Company

hirify.global is building an AI-powered health platform that combines laboratory testing, medical imaging, longitudinal data, and clinical guidance to help members understand and improve their health.

What you will do

• Own the semantic layer, including metrics, dimensions, and data models used as a trusted source of business data.
• Architect Databricks and GCP-based data systems for reliable AI-driven analytics agents.
• Build observability, testing, and alerting into production data pipelines.
• Enable self-serve analytics through dashboards and tooling for product, clinical, and business teams.
• Establish data modeling, documentation, naming, and code review standards across the data organization.
• Translate ambiguous business questions into data solutions and improve event logging with product engineering.

Requirements

• 8+ years of experience in analytics engineering, data engineering, or data architecture, with staff-level scope and impact.
• Deep SQL expertise and strong Python skills.
• Strong data modeling fundamentals and experience building documented, extensible models.
• Experience with modern data stack tools such as Databricks, Snowflake, BigQuery, Airflow, Looker, or Tableau.
• Experience building resilient, monitored, production-grade data systems.
• Strong communication skills for explaining technical tradeoffs to non-technical stakeholders.

Nice to have

• Health technology or regulated data experience, including HIPAA and PHI/PII handling.
• Experience with Unity Catalog, Delta Lake, or Spark.
• Experience building or integrating AI/LLM-powered analytics tools or data agents.
• GCP experience and familiarity with dbt.

Culture & Benefits

• Fully remote work within the stated Americas hiring regions.
• Flexible working hours.
• Competitive salary and benefits package.
• Collaborative environment focused on clear communication, ownership, execution, and data quality.
• Commitment to diversity, inclusion, and equal employment opportunity.