Data Quality Engineer

Location(s)

Details

Kemper is one of the nations leading specialized insurers. Our success is a direct reflection of the talented and diverse people who make a positive difference in the lives of our customers every day. We believe a high-performing culture valuable opportunities for personal development and professional challenge and a healthy work-life balance can be highly motivating and productive. Kempers products and services are making a real difference to our customers who have unique and evolving needs. By joining our team you are helping to provide an experience to our stakeholders that delivers on our promises.

POSITION 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 the accuracy reliability and integrity of business-critical data solutions. This role provides technical leadership across data testing validation reconciliation automation and quality assurance processes supporting analytics reporting and operational systems.

The ideal candidate is a self-motivated problem solver with strong intellectual curiosity deep expertise in data engineering and automated testing practices and a strong understanding of data governance security and compliance principles.

As a senior member of the data engineering team you will be responsible for developing scalable data validation frameworks ensuring data integrity across pipelines and platforms implementing automated testing strategies throughout the data lifecycle and supporting enterprise test environment strategy across complex data ecosystems.

Position Responsibilities:

• Design and Develop Data Testing Solutions

Build maintain and optimize automated data testing frameworks and validation pipelines that support enterprise reporting analytics and business applications using SQL Informatica IICS Snowflake and Python.

• Data Validation and Quality Assurance

Develop and execute data validation routines for extracts transformations and reporting datasets to ensure completeness accuracy consistency and reliability of enterprise data assets.

• Test Automation and Reconciliation

Design automated reconciliation processes between source and target systems including row count validation schema validation transformation testing and data profiling.

• Data Pipeline Quality Engineering

Partner with data engineering teams to embed testing and quality controls into ETL/ELT pipelines and CI/CD deployment processes across Snowflake Oracle and AWS environments.

• AI-Enabled Test Development and Automation

Leverage AI-assisted development tools and intelligent automation techniques to improve test coverage accelerate validation processes and enhance the efficiency of data quality engineering practices across enterprise data platforms.

• Test Environment Strategy and Management

Support and contribute to enterprise test environment strategy including environment planning test data management deployment coordination integration testing support and validation across development QA UAT and production environments.

• Data Governance and Compliance

Ensure compliance with enterprise data governance security and regulatory requirements by implementing data quality standards monitoring controls and audit-ready validation processes.

• Integration and Monitoring

Work with structured and semi-structured data formats (XML JSON) and cloud-native services to validate data ingestion transformation and integration processes across distributed platforms.

• Collaboration and Leadership

Collaborate with data engineers analysts QA teams and business stakeholders to define testing requirements improve data quality processes and support reporting solutions such as Power BI.

• Continuous Improvement

Recommend and implement improvements to data quality frameworks testing automation monitoring solutions governance processes and DataOps practices. Mentor junior team members and promote best practices in data quality engineering and testing.

Position Qualifications:

Required Skills and Experience

• Bachelors 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.
• Demonstrated expertise in:
  • SQL development and query tuning
  • Automated data testing and validation methodologies
  • Informatica and IICS for ETL and data integration testing
  • Snowflake data warehouse architecture and validation
  • Oracle database systems
  • Data reconciliation and data profiling techniques
  • Data modeling normalization and relational design
  • Handling and validating XML and JSON data structures
  • Building data quality solutions in AWS cloud environments
  • Python-based automation and testing frameworks
• Strong knowledge of test environment strategy including environment planning test data management deployment coordination integration testing support and validation across development QA UAT and production environments.
• Experience establishing and supporting end-to-end test strategies for enterprise data pipelines and distributed data platforms.
• Understanding of environment dependencies release validation processes and data synchronization considerations for large-scale data ecosystems.
• Experience developing automated test scripts and reusable validation frameworks.
• Strong understanding of ETL/ELT testing methodologies and end-to-end data flow validation.
• Strong problem-solving abilities and the capacity to work independently on complex technical challenges.
• Deep understanding of data security governance compliance and data quality best practices.
• High degree of self-motivation intellectual curiosity and commitment to continuous improvement.

Preferred Qualifications

• Insurance industry experience (P&C and/or Life).
• Experience working with IDMC/IICS.
• Experience with Data Vault 2.0 methodologies.
• Experience with data quality and observability tools.
• Experience with PowerShell or Python for automation and scripting.
• Knowledge of Git and CI/CD pipelines for automated testing and deployment.
• Exposure to hybrid or multi-cloud data architectures.
• Experience with Spark Kafka Airflow DBT and Infrastructure as Code frameworks.
• Experience implementing automated monitoring alerting and anomaly detection for data pipelines.
• Familiarity with DevOps and DataOps practices for enterprise data platforms.
• Experience supporting Power BI reporting and downstream analytics validation.
• Experience utilizing AI-assisted development and testing tools to accelerate test case generation validation scripting anomaly detection and quality engineering processes.
• Familiarity with AI-enabled data observability intelligent test automation and machine learning-assisted quality monitoring solutions.
• Experience leveraging generative AI tools for SQL validation automated documentation test optimization and pipeline quality analysis.
• The position can be worked hybrid out of a local Kemper office or remotely for a non-local candidate.
• Sponsorship is not accepted for this position.

The range for this position is $99000 to $164800. Whendeterminingcandidate offers we consider experience skills education certifications and geographic location among other factors. This job is eligible for an annual discretionary bonus and Kemper benefits (Medical Dental Vision PTO 401k etc.)

Kemper is proud to be an equal opportunity employer. All applicants will be considered for employment without attention to race color religion sex sexual orientation gender identity national origin veteran disability status or any other status protected by the laws or regulations in the locations where we operate. We are committed to supporting diversity and equality across our organization and we work diligently to maintain a workplace free from discrimination.

Kemper does not accept unsolicited resumes through or from search firms or staffing agencies. All unsolicited resumes will be considered the property of Kemper and Kemper will not be obligated to pay a placement fee.

Kemper will never request personal information such as your social security number or banking information via text or Kemper does not use external messaging applications like WireApp or Skype to communicate with you receive such a message delete it.

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