Staff Data Reliability Architect (AI)

TL;DR

Staff Data Reliability Architect (AI): Driving the transformation of data quality to data reliability across the organization by designing and building a centralized "Data Reliability Source of Truth" platform. Focus on redefining data quality metrics, automating reliability checks within CI/CD pipelines, and ensuring data fit-for-purpose for AI/ML models.

Location: Remote within the United States, with optional access to hubs in San Francisco, New York City, or Chicago.

Salary: $205,000–$277,000 USD (San Francisco Bay Area and New York City) or $179,000–$241,000 USD (All Other US Locations).

Company

hirify.global builds an industry-leading Healthcare Map® and AI-driven applications to reduce the global burden of disease.

What you will do

• Lead the conceptual shift from general "data quality" to Data Reliability across the entire organization.
• Design, prototype, and champion a single, centralized "Data Reliability Source of Truth" platform.
• Create the technical framework to automate the creation, deployment, and monitoring of Data Reliability checks throughout the product development lifecycle.
• Serve as a strategic thought partner to the Head of Data Quality and act as Chief Evangelist for the Data Reliability metric.
• Design the end-to-end architecture for the centralized "Data Reliability Source of Truth," ensuring scalability, performance, and API/dashboard consumption.
• Build and implement highly repeatable, configurable technical frameworks using Python/SQL/Spark to automate reliability checks into CI/CD pipelines.

Requirements

• 12+ years of cumulative experience in Data Engineering, Data Architecture, or Platform Engineering with a strong focus on enterprise data quality/governance/testing.
• 5+ years of experience leading or designing enterprise-wide, multi-team data quality frameworks.
• Expert-level proficiency in SQL and Python for efficient and complex data manipulation, engineering, and testing.
• Extensive experience designing and developing with distributed data processing platforms like Spark and pipeline orchestration tools like Airflow.
• Deep knowledge of modern cloud data warehousing environments (ideally Snowflake on AWS) and robust data modeling practices.
• Practical experience ensuring data is prepared and validated for AI/ML model consumption.

Culture & Benefits

• Hybrid work model with the power of choice and flexibility for individual employees.
• Roles may be completely remote based anywhere in the United States.
• Competitive total rewards package including medical, dental, and vision coverage.
• 401(k) Retirement Plan with company match.
• Paid time off for vacation, sickness, holiday, and bereavement.
• 100% company-paid life insurance and long-term disability insurance.
• Expectation to integrate AI into daily work, from summarizing documents to automating workflows.