Data Analyst II

Aureon•West Des Moines, IA

About The Position

The Data Analyst II collects, cleans, integrates, and analyzes structured and unstructured data from business systems, and develops dashboards, reports, scorecards, semantic models, and presentations. The role uses SQL, Microsoft SQL Server, Power BI, DAX, Power Query, Excel, and other approved tools, including AI-assisted analytics capabilities, to explore data, develop insights, and support reporting. The analyst partners with business users and technical stakeholders to define objectives and data requirements, document business rules, and translate needs into technical specifications and analytical solutions. The position develops and maintains reusable data pipelines and models, validates data and solutions, troubleshoots issues, and documents assumptions, lineage, definitions, and limitations. It also supports AI and machine learning prototypes, data migrations, system interfaces, and modernization efforts across on-premises and cloud platforms, while identifying opportunities for automation, standardization, and self-service analytics. The position requires strong analytical, communication, data storytelling, and organizational skills, along with attention to accuracy, documentation, confidentiality, information security, privacy, data governance, and responsible AI. Work is primarily indoors in an office environment and involves extended periods of sitting and frequent computer-screen use.

Requirements

Hands-on experience with data visualization, data modeling, data preparation, and data quality practices.
Strong analytical problem-solving skills and ability to connect data findings to business outcomes.
Ability to work independently under general supervision and collaborate 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 explain complex technical concepts in clear business language.
Attention to detail and commitment to data accuracy, documentation, reproducibility, and continuous improvement.
Ability to follow confidentiality, information security, privacy, data governance, and responsible AI standards.
Curiosity and willingness to learn emerging data and AI technologies.
Required tools and software: SQL, Microsoft SQL Server, Power BI, DAX, Power Query, and Excel.

Nice To Haves

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.
Exposure to cloud analytics platforms, Microsoft Fabric, Azure data services, AI-assisted analytics, or machine learning concepts desired.
Experience with Microsoft Fabric capabilities, including OneLake, Lakehouse, Warehouse, Data Factory, Dataflow Gen2, notebooks, semantic models, and Direct Lake.
Python or R experience for data analysis, automation, statistical analysis, or machine learning.
Experience with ETL or ELT development, source control, deployment pipelines, data cataloging, and data lineage practices.
Experience using Copilot or other approved AI tools for analytics while validating outputs and protecting confidential data.

Responsibilities

Collect, clean, integrate, and analyze structured and unstructured data from multiple business systems.
Create and publish dashboards, reports, scorecards, semantic models, and presentations using Power BI, Excel, and other approved visualization tools.
Use AI-assisted analytics tools, including Copilot and approved generative AI capabilities, to support data exploration, documentation, insight generation, and report development.
Identify trends, patterns, anomalies, and business drivers, and communicate findings as recommendations to 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 AI and machine learning use cases, assist with prototypes, and evaluate results for business value, data quality, security, privacy, and responsible AI considerations.
Support data migrations, system interfaces, and modernization initiatives involving on-premises and cloud data platforms.
Review processes and recommend improvements in automation, standardization, self-service analytics, and user experience.
Stay current on analytics, Microsoft Fabric, Power BI, AI, data governance, and visualization best practices.
Perform other duties and responsibilities as assigned and required.