Data Quality Engineer
About the Company
Insperity provides the most comprehensive suite of scalable HR solutions available in the marketplace with an optimal blend of premium HR service and technology. With more than 90 locations throughout the U.S., Insperity is currently making a difference for thousands of businesses and communities nationwide. We value diversity, inclusivity, and a sense of belonging, celebrating work and life events while partnering with clients and communities to drive success.
Insperity has earned recognition as a top place to work by organizations like Glassdoor and U.S. News & World Report, and we’re proud to be recognized for one of the country’s Top 50 Midsize Early Talent Programs through RippleMatch’s Campus Forward Awards.
Why Join Insperity?
- Flexibility: Over 80% of Insperity’s jobs offer flexibility to balance time with coworkers, clients, family, or community.
- Career Growth: Continuous learning programs, mentorship opportunities, and ongoing training are available.
- Well-Being: Total rewards package includes generous paid time off, top-tier medical, dental, and vision benefits, health & wellness support, and paid volunteer hours.
About the Role
This position is responsible for ensuring delivered products meet or exceed quality standards. The Data Quality Engineer implements quality mechanisms such as functional, integration, performance, security, and other tests as part of the Data Engineering organization. They ensure data quality metrics and indicators are available for easy consumption by internal and external customers and collaborate regularly with engineers, architects, analysts, data scientists, and business users across various data initiatives to maintain consistent data quality practices.
Responsibilities
- Participates in the engineering of data pipelines while ensuring quality metrics are sufficiently met.
- Partners with stakeholders to ensure quality dimensions are understood and engineered into solutions.
- Identifies, designs, and implements process improvements with a focus on automation, data delivery optimization, self-service, and scalability.
- Works seamlessly with stakeholders including Executives, Product Management, Centers of Excellence, and others.
- Participates in the creation and testing of large, complex data sets to meet business requirements.
- Ensures data security across all implementations, data centers, cloud providers, and client machines.
- Collaborates with team members to build and optimize data assets into an innovative competitive advantage.
Requirements
- Bachelor's Degree in Computer Science, a related field, or four years of related work experience in Business Intelligence/Data Engineering is required.
- Three to five years of professional experience in information systems, with at least one year of experience testing, developing, architecting, managing, or maintaining enterprise-grade software systems, database administration, or similar disciplines.
Skills
- Deep understanding and practical experience with common automated data quality and observability frameworks (e.g., Great Expectations, dbt, pytest, Talend, or similar).
- Deep understanding and practical experience with SQL.
- Ability to automate testing and integrate within CI/CD pipelines, primarily using Python.
- Understanding of various ‘big data’ management tools/techniques (e.g., Hadoop, Snowflake, Redshift, Tableau, PowerBI, Databricks).
- Strong consensus-building skills and the ability to find common ground across complex topics involving compromise and negotiation.
- Passion for learning, continuous improvement, and taking responsibility for acquiring new skills.
- Commitment to utilizing defined standards and processes.
- Strong verbal and written communication skills, with the ability to express complex technical concepts in business terms.
- Proactive at identifying and recommending areas for improvement and increased reliability.
- Ability to create technical documentation and share knowledge among team members.
- Understanding of data governance principles.