Business Data Analyst

PRI Global is seeking a Business Data Analyst to support the Enterprise Support data layer. The role owns data pipelines, models, SQL, dashboards, reporting, data governance, and quality initiatives while applying AI and LLM tooling to improve data workflows and extract insights from unstructured support data.

Responsibilities:

• Own the day-to-day health of the Enterprise Support data layer: pipelines, Hive tables, SQL, and dashboards
• Design and build data models for new reporting needs, proposing the approach rather than receiving a specification
• Maintain a documented source of truth for Enterprise Support metrics: definitions, ownership, and freshness
• Apply AI and LLM tooling to accelerate data work and to extract signal from unstructured support data such as ticket notes and resolution summaries
• Improve pipeline reliability and reduce manual effort over time through automation
• Monitor pipeline health, resolve failures and data quality issues, and run backfills
• Deliver recurring reporting (weekly, monthly, quarterly) and ad hoc analysis
• Apply and maintain standards for naming, documentation, and schema change management
• Proactively surface data quality, governance, and coverage gaps

Requirements:

• 6-7 years of experience in data analytics, business analytics, or analytics engineering
• Advanced SQL skills, including experience with large-scale distributed query engines such as Presto and Hive
• Demonstrated ownership of production data pipelines and data models, including design decisions rather than only maintenance
• Practical experience applying AI or LLM tooling within data workflows
• Experience with data modeling and dashboard development
• Ability to work independently and communicate status, recommendations, and blockers clearly in writing
• Data governance experience: metric catalogs, lineage, table ownership, and schema change management
• Experience supporting an IT, enterprise support, or technical operations organization
• Python or similar scripting experience for data automation
• Experience maintaining operational metrics and SLA reporting