Top Analysis Reporting Jobs in Charlotte, NC

Lead administration and support of enterprise analytics and BI platforms, including security/authentication, data access controls, metadata management, performance tuning, upgrades, and release validation. Enable self-service analytics through documentation, onboarding, governance, and support for analysts and data scientists. Advise business stakeholders with analytic insights, lead projects and teams, ensure compliance, and troubleshoot production issues.

Lead analytics and optimization for assigned digital merchandising divisions: aggregate insights, run competitive and customer analyses, present recommendations to senior leaders, guide and coach analysts, manage 6–10 projects, and support in-season tactical opportunities to improve omnichannel customer experience and digital performance.

Lead data validation and risk analytics practice, set strategic direction, manage multiple client engagements, and drive business development. Use Alteryx and Python for data integration, build dashboards in Power BI/Tableau, apply predictive analytics and statistical modeling, ensure data integrity/security, mentor teams, and cultivate executive client relationships.

Maintain and audit enterprise inventory and network data across advanced TV and digital ecosystems. Onboard inventory sources, manage mappings and naming conventions, troubleshoot data issues, collaborate with cross-functional teams, and support process improvements, testing, and documentation to ensure data quality and operational readiness.

The Senior Analyst in AML KYC will conduct detailed customer onboarding, monitor client relationships for compliance, and update KYC records while utilizing AI tools for efficiency.

Support a book of business by validating, transforming, and reconciling data, managing daily processing and file audits, generating reporting outputs for outreach, creating file configuration specs, resolving discrepancies with stakeholders, and driving process improvements to ensure regulatory compliance and operational efficiency.

Design, build, and operate cloud-native, domain-oriented data products and pipelines across Azure and AWS using Databricks and Snowflake. Lead migration from legacy platforms, implement batch and streaming processing with Spark, ensure security and governance compliance, promote best practices (CI/CD, testing, observability), and mentor junior engineers while collaborating with product, analytics, and security teams.

Partner with the Chief Administrative Officer to analyze financial, market, and operational data, produce executive-ready presentations and storylines, identify trends and risks, and recommend actions. Drive governance, reporting, and operational effectiveness using analytics and AI to support strategic decisions and improve speed, quality, and insights across product and practice leaders.

Perform complex analysis and modeling to detect and mitigate commercial payment fraud. Create and update business rules to reduce false positives, analyze alerts and trends, query large datasets, produce reports and dashboards, manage data governance and incident resolution, and collaborate with technology teams to implement process improvements and automation.

Lead feature delivery for Oracle-centric data pipelines and analytics platforms. Design, implement, and optimize PL/SQL packages, procedures, and ETL; automate jobs with Autosys and Unix shell scripting; perform data modeling, profiling, and performance tuning; mentor developers, support testing/UAT, and collaborate with stakeholders to ensure compliant, stable, high-quality database solutions.

Design, build, test, and support scalable data pipelines and reporting solutions for AML. Integrate, transform, and validate data, monitor production systems, troubleshoot issues, and collaborate with product, engineering, and business teams to ensure data quality, performance, and regulatory compliance.

Lead design and delivery of scalable, secure enterprise data engineering solutions. Set architecture and standards, mentor teams, implement cloud data platforms, data modeling, governance, quality controls, CI/CD, and liaise with executives and stakeholders to support analytics, compliance, and customer initiatives.

Support internal audit teams by executing data analytics to identify anomalies, trends, and risks. Validate, extract, and prepare data, build visualizations and recurring reports, document methodologies, and present findings with actionable recommendations to drive audit and business decisions.