Senior Data Quality Engineer - Remote Testing & Validation

Kemper; Hartford (CT); Hybrid; USD 99,000 - 164,800; Full time

Benefits offered by this job

401k

Health insurance

Paid time off

Tuition assistance

Job summary

Kemper is seeking a Data Quality Engineer to design, build, and optimize enterprise data testing frameworks. You will validate data across pipelines, implement automated testing strategies, and support data governance within Snowflake, Oracle, and AWS environments.

The role emphasizes collaboration with data engineers, QA teams, and business stakeholders to ensure data integrity for analytics, reporting (Power BI), and production systems. Hybrid work options are available.

Qualifications

• Degree or equivalent in CS/IS or related field.
• 6+ years in data engineering, testing, or DB development.
• Strong SQL and query tuning skills.
• Experience with automated data testing and validation methods.
• Hands-on with Informatica and IICS for ETL testing.
• Snowflake data warehouse validation and Oracle DB experience.

Responsibilities

• Design and implement automated data testing frameworks for enterprise data assets.
• Develop data validation routines for extracts, transformations, and reports.
• Create automated reconciliation between source and target systems.
• Embed testing controls into ETL/ELT pipelines across Snowflake, Oracle, AWS.
• Leverage AI-assisted tools to improve test coverage and speed up validation.
• Support test environment strategy across development, QA, UAT, and prod.

Skills

SQL development

Automated testing

Informatica

IICS

Snowflake

Oracle

Python

Data governance

Education

Bachelor’s degree in CS / IS

Tools

Informatica

IICS

Snowflake

Oracle

AWS

Power BI

Job description

Kemper is seeking a Data Quality Engineer to design, build, and optimize enterprise data testing frameworks. You will validate data across pipelines, implement automated testing strategies, and support data governance within Snowflake, Oracle, and AWS environments.

The role emphasizes collaboration with data engineers, QA teams, and business stakeholders to ensure data integrity for analytics, reporting (Power BI), and production systems. Hybrid work options are available.