What are the responsibilities and job description for the Business Intelligence Analyst position at Prime Capital Financial?
Overview: The Business Intelligence Analyst supports the development, reliability, and continuous improvement of Prime Capital Financial’s business intelligence, data integration, and automation environment. Working alongside other BI analysts as a peer and under BI leadership, this person turns information from across the business into trusted datasets, efficient workflows, and actionable insights. Our team works across the full data lifecycle, from source-system integrations and production data pipelines to reporting, analytics, and emerging AI-enabled applications. We seek a hands-on, resourceful problem-solver who brings practical Python and visualization skills, intellectual curiosity, and a willingness to learn. Expertise in every platform is not expected on day one.
KEY RESPONSIBILITIES:
Data Engineering, Integration, and Quality
• Build, maintain, and improve data ingestion, transformation, and automation workflows using Python, SQL, Alteryx, and related tools.
• Integrate data from internal applications, partner/vendor APIs, and file-based feeds, including CRM, portfolio management, and other financial services systems.
• Query and work with datasets in Snowflake, Amazon Redshift, and PostgreSQL while maintaining reliable, well-structured data for downstream use.
• Monitor production jobs and refreshes, diagnose failures and anomalies, implement data quality checks, and document business rules, metric definitions, and procedures.
Analytics, Reporting, and Business Insights
• Build and maintain clear, accurate visualizations and recurring reports in Tableau, which serves as our firm’s primary reporting and visualization layer.
• Analyze business and operational performance, including assets, revenue, growth, retention, and advisor or client activity. The ability to glean new insights is always desirable.
• Translate stakeholder questions into analytical requirements, explain findings, and communicate limitations and recommendations.
Automation, Cloud Technologies, and Emerging AI
• Identify repetitive work and develop maintainable automations that improve efficiency, consistency, and data accuracy.
• Support cloud-based integrations, workflows, and processing systems as team priorities require.
• Help prepare and validate trusted data for internal AI-enabled applications, including content extraction and connections to business systems.
Creative Problem Solving, Innovation, and Continuous Improvement
• Approach ambiguous technical and business challenges with curiosity, persistence, and original thinking. Investigate root causes rather than applying temporary fixes.
• Propose, prototype, and evaluate better approaches to data pipelines, analytics, reporting, and operational processes while weighing reliability, maintainability, and business impact.
• Challenge inefficient processes constructively, seek feedback, stay current with new technologies, and turn lessons learned into practical improvements.