Senior Data Quality Engineer: AI-Driven Testing & Validation

Kemper Corporation

Chicago (IL)

Hybrid

USD 99,000 - 165,000

Full time

14 days+

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Benefits offered by this job

Health insurance

401k matching

Tuition assistance

Paid time off

Job summary

Kemper is seeking a Data Quality Engineer specializing in Data Testing and Quality Engineering to design, implement, and optimize validation frameworks for enterprise data solutions. You will lead data testing across pipelines, automation, and governance, partnering with data engineers, analysts, and business stakeholders to ensure data integrity and reliable analytics.

You will design validation routines, automate reconciliation, and advance testing strategies across Snowflake, Oracle, and AWS

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.
Experience with SQL development and query tuning.
Experience with automated data testing and validation methodologies.
Experience with Informatica and IICS for ETL and data testing.
Experience with Snowflake data warehouse and Oracle databases.
Proficiency in Python-based automation and testing frameworks.
Understanding of data governance, security, and compliance practices.
Strong problem-solving and independent-working abilities.

Responsibilities

Design and develop data testing solutions across enterprise reporting, analytics, and business applications.
Build and optimize automated data testing frameworks and validation pipelines using SQL, Informatica, IICS, Snowflake, and Python.
Develop data validation routines for extracts, transformations, and reporting datasets.
Create automated reconciliation processes between source and target systems, including row count and schema validation.
Embed testing and quality controls into ETL/ELT pipelines and CI/CD deployment in Snowflake, Oracle, and AWS environments.
Leverage AI-assisted development tools to improve test coverage and efficiency across data platforms.
Contribute to enterprise test environment strategy and data management across development, QA, UAT, production.
Ensure data governance and compliance through validation and monitoring controls.
Collaborate with data engineers, analysts, QA, and stakeholders to support Power BI reporting.