Data Analyst II

Aureon•West Des Moines, IA

1d•Onsite

About The Position

This role involves collecting, cleaning, integrating, and analyzing data from various business systems using tools like SQL, Python, and Power Query. The analyst will create and publish reports and dashboards using Power BI, Excel, and other visualization tools. A key aspect of the role is applying AI-assisted analytics, including Copilot features and generative AI, to enhance data exploration, documentation, insight generation, and report development. The position requires identifying trends, patterns, and business drivers, and translating these findings into actionable recommendations for both technical and non-technical audiences. Collaboration with business users to define data requirements, document business rules, and translate needs into technical specifications is essential. The role also includes developing and maintaining data pipelines, models, and quality controls, validating data accuracy, testing solutions, and troubleshooting issues. Exploring AI and machine learning use cases, supporting prototypes, and evaluating their business value, data quality, security, and privacy are also part of the responsibilities. Additionally, the analyst will support data migrations and modernization initiatives, review processes for automation opportunities, and stay current with analytics and AI best practices. Other duties as assigned are also included.

Requirements

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.
SQL
Microsoft SQL Server
Power BI
DAX
Power Query
Excel

Nice To Haves

Microsoft Fabric, including OneLake, Lakehouse, Warehouse, Data Factory, Dataflow Gen2, notebooks, semantic models, and Direct Lake.
Python or R for data analysis, automation, statistical analysis, or machine learning.
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.
Use Microsoft Fabric capabilities such as OneLake, Lakehouse, Warehouse, Data Factory, notebooks, data pipelines, Dataflow Gen2, and Direct Lake where appropriate.

Responsibilities

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.