Senior Data Quality & Validation Analyst (Hybrid/Remote)

Kemper Corporation; Alpharetta, Northern (GA, KY); Hybrid; USD 89,000 - 148,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

Vision benefits

PTO

401k

Job summary

Kemper Corporation is seeking a Senior Data Systems Analyst to validate data quality across enterprise platforms and ensure regulatory compliance. You will partner with data engineers, product owners, and controls teams to define testing strategies, validate data movements, and improve data quality practices.

The role emphasizes independent quality assurance, end-to-end workflow testing, and collaboration across data engineering and operational teams in a hybrid work setup.

Qualifications

• Bachelor's degree in a related field and 6+ years of data quality and analytics experience.
• Experience with data warehousing, governance, testing, and regulatory validation in insurance.
• Strong SQL, data profiling, and data lineage troubleshooting abilities.

Responsibilities

• Investigate production data incidents and perform root cause analysis.
• Develop testing strategies and validation documentation for data platforms.
• Collaborate with data engineers to implement automated testing and QA practices.
• Lead end-to-end data workflow validation across ETL/ELT processes.
• Support governance, compliance, and audit data validation activities.

Skills

Data quality analysis

Data warehousing

Business systems analysis

Data governance

Quality assurance

Data testing

Business process validation

Education

Bachelor's degree in Information Systems, Computer Science, Data Analytics, Business Analytics, or related field

Tools

Snowflake

Oracle

SQL Server

Informatica/IICS

Power BI

Python

XML/JSON APIs

Job description

Kemper Corporation is seeking a Senior Data Systems Analyst to validate data quality across enterprise platforms and ensure regulatory compliance. You will partner with data engineers, product owners, and controls teams to define testing strategies, validate data movements, and improve data quality practices.

The role emphasizes independent quality assurance, end-to-end workflow testing, and collaboration across data engineering and operational teams in a hybrid work setup.