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Lead Data Analyst

Job in Honolulu, Honolulu County, Hawaii, 96814, USA
Listing for: Stash Talent Services
Full Time position
Listed on 2026-06-12
Job specializations:
  • IT/Tech
    Data Analyst, Business Systems/ Tech Analyst, Data Science Manager, Data Warehousing
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

We are seeking a Lead Data Analyst to lead enterprise analytics initiatives, develop advanced Power BI solutions, and drive data-informed business decisions. This role will focus on analytics governance, reporting optimization, AI-assisted insights, and cross-functional business partnership. The ideal candidate has strong SQL and Power BI expertise, experience with advanced analytics, and the ability to influence stakeholders through data-driven insights.

Responsibilities
  • Lead enterprise analytics standards, governance, and reporting accuracy
  • Build advanced Power BI dashboards and optimized data models
  • Develop AI-assisted insights including forecasting, anomaly detection, and automation
  • Write and optimize complex SQL queries and analytical datasets
  • Partner with business leaders to translate data into actionable insights
  • Mentor analytics team members and influence data-driven culture
Qualifications
  • Associate’s or Bachelor’s degree preferred or equivalent experience.
  • Master’s degree in Analytics, Data Science, Business Analytics, Information Systems, or a related discipline preferred.
  • Professional certifications in analytics or business intelligence (e.g., Power BI, Microsoft Data Analytics, SQL, D365, data modeling) preferred.
  • At least 5 years of related experience in analytics, business intelligence, or data analysis experience, with demonstrated impact on business decision-making.
  • Advanced proficiency in Power BI, including semantic modeling, DAX, and performance optimization.
  • Strong SQL expertise, including development and optimization of complex queries and analytical datasets.
  • Experience applying advanced analytics or AI-assisted techniques (e.g., forecasting, trend analysis, anomaly detection, automation) in a production business environment.
  • Experience supporting analytics in operations driven environments such as food distribution, supply chain, logistics, wholesale, or financial analysis preferred.
  • Demonstrated ability to work as a senior individual contributor, providing technical leadership, mentoring analysts, and influencing cross-functional analytics adoption without formal people management.
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