Finance Data Analyst

Haag, a Salas O'Brien Company•,

97d•Remote

About The Position

The Finance Data Analyst will be responsible for collecting, analyzing, and presenting data to support business decision-making. This role involves designing ETL data flows, developing business intelligence dashboards, creating user-friendly forms in SharePoint, and visualizing data through reports and charts. The ideal candidate will ensure data integrity, develop efficient data solutions, and collaborate with various teams to meet business needs.

Requirements

Bachelor’s degree in Mathematics, Computer Science, Business or related field or equivalent years of relevant experience in lieu of degree
Seven (7)+ years of progressive data reporting and analytics experience
Ability to work independently and manage multiple tasks simultaneously
Strong attention to detail and commitment to data integrity
Ability to communicate complex data insights in a clear and concise manner to non-technical stakeholders
Strong proficiency in Excel (Pivot Tables, Macros, Financial Modeling)
Knowledge of data warehousing
Experience with data visualization tools (Tableau, etc.)
Strong analytical and problem-solving skills
Proficiency in the following applications: Deltek Vantagepoint, JavaScript, Microsoft Power Automate, Microsoft SharePoint, Microsoft SQL Server, Microsoft Visual Studio, SQL Server Management Studio (SSMS), SQL Server Reporting Services (SSRS)

Responsibilities

Collect and compile data from various sources, ensuring accuracy and completeness.
Maintain and update organizational dashboards.
Analyze data to identify trends, patterns, and anomalies.
Develop and maintain regular reports, dashboards, and visualizations to support decision-making.
Create ad hoc reports as needed for special projects or inquiries.
Perform data validation and cleaning to ensure data quality.
Monitor data quality metrics and implement improvements as necessary.
Work closely with cross-functional teams to understand data needs and provide analytical support.
Present findings and insights to stakeholders in a clear and understandable format.
Identify opportunities to streamline data collection and reporting processes.
Implement automation where possible to improve efficiency and reduce errors.
Ensure all data handling practices comply with company policies and relevant regulations.
Maintain the confidentiality and security of sensitive data.