Data Analyst II

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field preferred; or 4+ years of experience in data analytics or a related discipline in lieu of a degree
• Experience creating reports, dashboards, and deliverables to enable data-driven decision-making
• Experience in SQL with experience in data modeling
• Hands-on experience with Tableau
• Experience enabling BI tools through the design and delivery of secure, reliable data pipelines, curated data models, and performant data access layers
• Experience enhancing data reliability by creating, updating, validating SQL tables, ensuring accuracy across reporting and operational systems.
• Demonstrated ability to work collaboratively with both technical and non-technical stakeholders
• Requests:
• Must be a

Benefits

Additional Information

The Data Analyst II serves as a subject matter expert on assigned data domains and source systems, partners with stakeholders to define metrics and reporting needs, and develops scalable analytical solutions that improve accuracy, efficiency, and business understanding. This role is expected to support enterprise reporting, ad hoc analysis, data quality validation, process improvement, and documentation while helping business leaders interpret trends, risks, and opportunities. Metrics, Business Analysis & Decision Support Determine, implement, and evaluate business metrics to meet ongoing organizational, operational, financial, clinical, or customer information needs. Translate business questions into analytical approaches, including defining data requirements, selecting appropriate methods, and communicating results in a clear and actionable manner. Support forecasting, data mining, variance analysis, financial analysis, operational analysis, and other advanced analytics efforts as needed. Produce ad hoc reports and analyses by gathering, transforming, and interpreting data from multiple systems. Support mission-critical, strategic, and time-sensitive reporting projects, tasks, and initiatives. Data Analysis, SQL & Python Analyze complex datasets using SQL, Python, and business intelligence tools to identify trends, patterns, risks, opportunities, and performance drivers. Gather, integrate, clean, and validate data from disparate sources, including enterprise data warehouses, operational systems, financial systems, and external data sources. Build repeatable analytical workflows and reporting processes using SQL, Python, automation tools, and documented procedures to reduce manual effort and improve consistency. Pursue opportunities to generate more business insights to advance data-driven decision making across the business. Business Intelligence, Reporting & Visualization Develop and maintain dashboards, reports, and analytical tools using Tableau and other BI platforms, ensuring results are accurate, timely, intuitive, and aligned to business needs. Prepare executive-ready summaries, presentations, and visualizations that communicate analytical findings to technical and non-technical audiences. Using available tools, including next generation platforms and emerging technologies, perform Data Analytics development and testing to test suitability and advance analytics capabilities within the business. Assist the business in interpreting dashboards, reports, and data products to increase data literacy and assist in decision making. Data Quality, Troubleshooting & Governance Support Troubleshoot questions and issues related to data, reporting, dashboards, source systems, definitions, and metric logic. Validate data quality, reconcile results across systems, and identify opportunities to improve data reliability and reporting accuracy. Create and maintain documentation, including metric definitions, business rules, data sources, transformation logic, report instructions, and standard operating procedures. Stakeholder Partnership & Data Product Delivery Partner with stakeholders to gather requirements, define success measures, and deliver scalable data products that support decision-making. Cross-train team members on metrics, reporting processes, analytical methods, and dashboard usage. Provide hands-on guidance to junior team members as needed. Look for solutions to democratize data and enable self-service data analytics across the business. Process Improvement, Automation & Self-Service Enablement Identify opportunities for process improvement, automation, self-service reporting, and more effective use of organizational data. Stay current on emerging AI/ML data engineering tools and best practices, proactively recommending improvements to existing workflows Mentorship & Collaboration Provide technical guidance and mentorship to junior data engineers and analysts, fostering a culture of learning and continuous improvement Contribute to team-wide documentation, code reviews, and engineering standards Collaborate effectively in a fully remote environment, maintaining clear and proactive communication across teams

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