Data Analyst

Description

We are looking for a Data Analyst to join a printing and publishing organization in Shakopee, Minnesota, where this Long-term Contract position will help strengthen reporting, data accuracy, and business insight across enterprise platforms. This role focuses on examining complex information from order, billing, shipping, and operational systems so teams can make better decisions with greater confidence. The ideal candidate brings strong analytical depth, practical experience with large datasets, and the ability to turn technical findings into meaningful recommendations for both IT and business stakeholders.

Responsibilities:
Examine data from enterprise, order management, and operational platforms to support reporting and analysis across quote-to-cash activities such as quoting, invoicing, shipping, and billing.
Gather, transform, and reconcile information from multiple sources, including Oracle-based environments, internal business applications, and external logistics or shipping systems.
Investigate reporting discrepancies by identifying broken data relationships, integration weaknesses, and process issues that affect downstream accuracy.
Perform advanced analysis using SQL, Python, and Excel to uncover trends, exceptions, and root causes within high-volume datasets.
Cleanse, standardize, and match structured and unstructured records across systems to improve consistency and usability of business data.
Apply validation methods, reconciliation logic, and fuzzy matching techniques to strengthen data quality and improve alignment between connected platforms.
Build, update, and maintain dashboards and visual reports using tools such as Power BI, Tableau, or similar business intelligence solutions.
Collaborate with IT teams, data engineers, and business partners to translate analytical findings into practical system and process enhancements.
Contribute to ongoing data governance efforts and support broader initiatives focused on improving data quality, reporting reliability, and enterprise data management.

Requirements

5+ years of experience in data analysis within IT, enterprise systems, or application-focused environments.
Strong hands-on expertise with SQL, Python, and advanced Excel for complex analysis and data preparation.
Experience working with Oracle and other integrated business systems in a cross-functional enterprise setting.
Solid understanding of data movement, system interfaces, and core data architecture principles.
Proficiency with reporting and visualization platforms such as Power BI or Tableau.
Demonstrated ability to analyze incomplete, inconsistent, or unstructured data and produce accurate, actionable insights.
Strong communication skills with the ability to explain technical findings clearly to both technical and non-technical audiences.
Background in data analysis related to fraud analytics, anti-fraud efforts, fraud investigation, or suspected fraud is a plus.

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