Business Intelligence Analyst
Job Summary
The Business Intelligence Analyst plays a critical role in transforming data into meaningful, accurate, and actionable insights that support strategic decision-making, operational performance, and financial discipline across the organization. This role is responsible for designing and delivering scalable business intelligence solutions, including interactive dashboards, reporting tools, data models, and analytical frameworks that help leaders better understand trends, measure performance, identify opportunities, and make informed decisions. This position serves as both a technical analytics resource and a cross-functional business partner, working closely with Finance, Operations, HR, Marketing, IT, and senior leadership to translate complex business questions into reliable data solutions.
Essential Job Functions
Business Intelligence, Reporting & Dashboard Development
Design, build, and maintain interactive dashboards, visualizations, and self-service reporting tools using Sigma, Power BI, , or similar platforms.
Translate raw data from accounting, financial systems, operations, HR, marketing, and other business areas into clear, accurate, and actionable reporting outputs.
Develop recurring and ad hoc reports that communicate KPIs, trends, variance analysis, performance drivers, and business implications.
Data Engineering, Modeling & Integration
Design, build, and maintain scalable ETL/ELT data pipelines using SQL, Python, PySpark, cloud-based orchestration tools, APIs, databases, flat files, and third-party platforms.
Build and maintain data models, schemas, semantic layers, and warehouse structures, including dimensional models, to support consistent and scalable reporting and analytics.
Write and optimize complex SQL queries, tune data workflows, and improve data storage, retrieval, processing performance, and reliability across reporting environments.
Advanced Analytics & Emerging Technology Support
Support forecasting, segmentation, optimization, experimentation, and data science initiatives by preparing reliable datasets, curated inputs, and scalable data assets.
Evaluate and apply AI-enabled analytics tools, including generative AI and large language models, to improve reporting automation, data exploration, insight generation, and business productivity.
Use AI and LLM-enabled tools responsibly by following appropriate data privacy, security, governance, validation, and documentation standards.
Business Partnership & Performance Insights
Partner with leaders and stakeholders across Finance, Operations, HR, Marketing, IT, analytics, and senior leadership to understand business needs, define reporting requirements, and align data initiatives with organizational priorities.
Define and standardize key performance indicators, support budgeting, forecasting, and financial performance analysis, and identify opportunities for cost optimization, revenue growth, and operational efficiency.
Data Governance, Quality & Process Improvement
Ensure data integrity, consistency, security, and compliance by implementing validation checks, access controls, monitoring, documentation, and governance standards.
Perform data validation, cleansing, reconciliation, and root-cause analysis to resolve data discrepancies, reporting issues, and process gaps.
Automate manual reporting processes, improve data workflows, document business logic and reporting standards, and stay current with BI, analytics, AI, and data engineering technologies.