Senior Data Quality Engineer - Remote & Automation Leader

Kemper; United States; Hybrid; USD 99,000 - 165,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

401k

Job summary

Kemper is seeking a Data Quality Engineer specializing in data testing and quality engineering to design, implement, and optimize enterprise data validation frameworks that ensure accuracy and reliability of critical data solutions. You will lead testing practices across data pipelines and analytics environments.

The ideal candidate has deep data engineering expertise, experience with automated testing, governance, and compliance, and the ability to mentor teammates in DataOps practices within a

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field; equivalent work experience considered.
• 6+ years of experience in data engineering, data testing, or database development.
• Strong SQL development and query tuning abilities.
• Experience with Informatica and IICS for ETL testing and data integration.
• Proven ability to build data validation and automated testing frameworks.

Responsibilities

• Design and develop automated data testing frameworks and validation pipelines across analytics and reporting platforms.
• Implement data validation routines for extracts, transformations, and reporting datasets to ensure data quality.
• Create automated reconciliation processes between source and target systems including schema validation.
• Collaborate with data engineering on ETL/ELT pipelines in Snowflake, Oracle, and AWS environments.
• Leverage AI-assisted tools to improve test coverage and automation efficiency.

Skills

SQL development

Automated data testing

Informatica/IICS

Snowflake

Oracle

Data reconciliation

Python automation

Power BI support

Education

Bachelor’s degree in Computer Science or related field

Tools

Informatica

IICS

Snowflake

Oracle

Python

Job description

Kemper is seeking a Data Quality Engineer specializing in data testing and quality engineering to design, implement, and optimize enterprise data validation frameworks that ensure accuracy and reliability of critical data solutions. You will lead testing practices across data pipelines and analytics environments.

The ideal candidate has deep data engineering expertise, experience with automated testing, governance, and compliance, and the ability to mentor teammates in DataOps practices within a