Data Analyst II

• Collect, clean, integrate, and analyze structured and unstructured data from multiple business systems using SQL, Python, Power Query, or other approved tools.
• Create and publish dashboards, reports, scorecards, semantic models, and presentations using Power BI, Excel, and other approved visualization tools.
• Apply AI-assisted analytics tools, including Copilot features and approved generative AI capabilities, to accelerate data exploration, documentation, insight generation, and report development.
• Identify trends, patterns, anomalies, and business drivers, then translate findings into clear recommendations for technical and nontechnical audiences.
• Partner with business users to understand objectives, define data requirements, document business rules, and translate needs into technical specifications and analytical solutions.
• Develop and maintain reusable data pipelines, dimensional models, semantic models, calculations, and data quality controls.
• Validate data accuracy, test solutions, troubleshoot issues, reconcile results, and document assumptions, lineage, definitions, and limitations.
• Explore practical AI and machine learning use cases, assist with prototypes, and evaluate results against business value, data quality, security, privacy, and responsible AI expectations.
• Support data migrations, system interfaces, and modernization initiatives involving on-premises and cloud data platforms.
• Review current processes and recommend opportunities for automation, standardization, self-service analytics, and improved user experience.
• Stay current on analytics, Microsoft Fabric, Power BI, AI, data governance, and visualization best practices.
• Other duties and responsibilities as assigned and required.
• Bachelor's degree from a four-year university in data analytics, computer science, information systems, statistics, business, or a related field desired.
• Two or more years of related experience in data analysis, analytics, business intelligence, reporting, or data administration desired.
• Hands-on experience with data visualization, data modeling, data preparation, and data quality practices.
• Exposure to cloud analytics platforms, Microsoft Fabric, Azure data services, AI-assisted analytics, or machine learning concepts desired.
• Strong analytical problem-solving skills with the ability to connect data findings to business outcomes.
• Ability to work independently under general supervision while collaborating effectively with business and technical stakeholders.
• Ability to plan and prioritize work, manage multiple assignments, and meet deadlines in a changing environment.
• Strong written, verbal, presentation, and data storytelling skills.
• Ability to translate complex technical concepts into clear business language.
• Attention to detail and commitment to data accuracy, documentation, reproducibility, and continuous improvement.
• Ability to adhere to confidentiality, information security, privacy, data governance, and responsible AI standards.
• Curiosity and willingness to learn emerging data and AI technologies.

None flagged.