Data Visualization Engineer

Keystone is a national insurance brokerage that supports independent agencies through operational, financial, technological, and analytics resources. The Data Visualization Engineer will build enterprise-grade Power BI business intelligence solutions, apply AI and Generative AI capabilities to analytics, and transform complex data into actionable insights and scalable self-service analytics experiences.

Responsibilities:

• Design, develop, and maintain sophisticated Power BI dashboards, reports, scorecards, and analytical applications for business and executive audiences
• Translate complex business requirements into intuitive and actionable analytical experiences
• Develop scalable semantic models, measures, calculated columns, and business logic using DAX
• Build efficient data transformations using Power Query
• Apply appropriate dimensional modeling techniques, including star schema, fact and dimension design, hierarchies, and reusable semantic models
• Design dashboards using strong principles of data visualization, UX/UI, information hierarchy, and data storytelling
• Optimize Power BI solutions for performance, scalability, usability, and maintainability
• Implement drill-through, bookmarks, tooltips, dynamic measures, field parameters, conditional formatting, and other advanced Power BI capabilities where appropriate
• Use AI and Generative AI tools to accelerate dashboard and report development, requirements interpretation, DAX development, documentation, testing, and troubleshooting
• Leverage AI-assisted analytical capabilities to help identify patterns, anomalies, trends, correlations, and business insights within enterprise data
• Create intuitive analytical experiences that allow users to move beyond static reporting toward conversational and AI-assisted data exploration
• Understand how to formulate effective prompts and business questions to obtain reliable analytical results from AI-powered tools
• Explore appropriate use of natural-language querying, AI-generated narratives, automated summaries, anomaly detection, forecasting, and intelligent visualization recommendations
• Identify opportunities where AI can reduce manual reporting effort and improve analyst and business-user productivity
• Help establish reusable patterns and best practices for responsible AI adoption within BI and analytics
• Stay current with advancements in AI-enabled analytics and recommend capabilities that can provide measurable business value
• Connect Power BI to data from cloud platforms, databases, APIs, data warehouses, lakehouses, Excel/SharePoint sources, and other enterprise applications
• Collaborate with data engineering teams to define appropriate datasets and data models for analytics consumption
• Perform data profiling, validation, reconciliation, and troubleshooting to ensure dashboard accuracy
• Develop efficient incremental refresh and data refresh strategies
• Understand upstream/downstream data dependencies and assist with root-cause analysis of data-quality issues
• Implement appropriate Row-Level Security (RLS) and data-access controls
• Follow organizational standards for workspace management, deployment, naming conventions, documentation, and governance
• Participate in development, testing, deployment, and production-support processes
• Promote reusable datasets and governed semantic models rather than creating unnecessary duplicate data models
• Partner with data governance and security teams to ensure appropriate handling of sensitive or confidential information

Requirements:

• Bachelor's degree in Computer Science, Information Systems, or related field required
• Minimum of 3 years of experience in Business Intelligence, Data Analytics, or Data Visualization
• Proven hands-on experience developing and maintaining solutions using Microsoft Power BI
• Strong SQL skills, with the ability to write, optimize, and troubleshoot complex queries
• Experience working with modern cloud data platforms such as Databricks, Snowflake, or similar technologies
• Experience designing dimensional data models and enterprise semantic models
• Demonstrated ability to optimize Power BI reports and datasets for performance
• Strong understanding of data quality, validation, and reconciliation
• Experience translating ambiguous business requirements into effective analytical solutions
• Demonstrated proficiency using Generative AI or AI-assisted tools in analytics and BI workflows
• Ability to critically evaluate AI-generated output for accuracy and business context
• Strong analytical, problem-solving, and critical reasoning skills
• Excellent written and verbal communication skills, including the ability to present technical concepts and data-driven insights to non-technical stakeholders