Senior Data Systems Analyst

Location(s):
Alpharetta, Georgia;
Chicago, Illinois;
Cincinnati, Ohio;
Dallas, Texas;
Des Moines, Iowa;
Jacksonville, Florida; P&C-Butterfield Road–Downers Grove, IL.

Kemper is seeking a highly analytical and detail‑oriented Data Systems Analyst to provide independent validation and quality assurance across enterprise data platforms, business processes, and reporting solutions. This role is responsible for ensuring the accuracy, completeness, reliability, and regulatory compliance of critical business data and end-to-end data workflows. The Data Systems Analyst serves as an independent quality function within the Data Engineering organization, partnering closely with business stakeholders, data engineers, data architects, product owners, compliance teams, and operational teams to validate business requirements, identify data quality risks, and ensure enterprise data solutions meet business and regulatory expectations.

• Investigate production data incidents and quality issues.
• Perform root cause analysis and identify corrective and preventive actions.
• Partner with engineering and operational teams to prioritize remediation activities.
• Track recurring issues and recommend long‑term quality improvements.

• Develop and maintain comprehensive testing strategies for enterprise data platforms and business‑critical processes.
• Create test cases, test scenarios, traceability matrices, and validation documentation.
• Establish risk‑based testing approaches to ensure appropriate coverage of critical business functions.
• Define quality gates and acceptance criteria for data products and platform releases.

• Collaborate with data engineering teams to develop reusable testing assets and automated validation processes.
• Support implementation of automated testing frameworks for data validation, reconciliation, regression testing, and quality monitoring.
• Promote quality engineering best practices across the data organization.

• Conduct regression testing across enterprise systems following enhancements, migrations, platform upgrades, and releases.
• Assess downstream impacts of system and data changes.
• Validate production deployments and release readiness.

• Support performance, scalability, reliability, recoverability, and operational readiness testing.
• Validate system behavior under expected and peak business workloads.
• Assess data processing performance and service‑level requirements.

• Design and execute test plans for complex business and data workflows spanning multiple applications, databases, integrations, and reporting platforms.
• Validate data movement across source systems, ETL/ELT processes, data warehouses, reporting environments, and downstream consumers.
• Perform system integration testing, user acceptance testing support, and production validation activities.

• Partner with business stakeholders, product owners, and data engineering teams to clarify and refine requirements.
• Translate business requirements into testable scenarios and validation criteria.
• Challenge assumptions and identify requirement gaps, ambiguities, and potential quality risks early in the delivery lifecycle.

• Develop and monitor data quality KPIs, controls, and scorecards.
• Support enterprise data quality governance initiatives.
• Contribute to the establishment of data quality standards, policies, and operating procedures.
• Drive continuous improvement of data quality management practices.

• Independently validate critical business processes and supporting data workflows across operational, analytical, and regulatory systems.
• Evaluate end‑to‑end business process execution to ensure data integrity, accuracy, completeness, and consistency throughout the data lifecycle.
• Identify control gaps, data risks, process deficiencies, and opportunities for quality improvement.

• Perform independent…