Data Quality Engineer: Build Reliable Data Pipelines

Insperity Services, L.P.; Kingwood (WV); On-site; USD 90,000 - 120,000; Full time

Job summary

Insperity is seeking a Data Quality Engineer to ensure data products meet quality standards across pipelines and platforms. You will implement tests, monitor metrics, and work with data scientists, engineers, and business users to sustain reliable data delivery.

The role emphasizes automation, governance, and collaboration with executives and centers of excellence to optimize data assets and enable strategic decision-making across client environments.

Qualifications

• Bachelor's degree in CS or related field or 4 years of related work experience.
• 3–5 years of professional experience in information systems with at least 1 year in testing, developing, architecting, or maintaining enterprise software systems.
• Deep experience with automated data quality and observability frameworks (e.g., Great Expectations, dbt, pytest, Talend).
• Strong SQL skills and ability to automate testing within CI/CD pipelines using Python.
• Familiarity with big data tools (Hadoop, Snowflake, Redshift, Tableau/PowerBI, Databricks).
• Excellent written and verbal communication, cross-functional collaboration, and eager to learn and improve.”

Responsibilities

• Participates in building data pipelines while ensuring quality metrics are met.
• Collaborates with Executives, Product Management, and Analysts to align quality dimensions.
• Designs and implements automation to improve data delivery and scalability.
• Maintains documentation and promotes data governance across platforms.
• Identifies areas for process improvements and reliability enhancements.

Skills

Data quality testing

SQL

Python

CI/CD automation

Big data concepts

Education

Bachelor's Degree in Computer Science

Tools

Great Expectations

dbt

pytest

Talend

Tableau

PowerBI

Databricks

Hadoop

Snowflake

Redshift

Job description

Insperity is seeking a Data Quality Engineer to ensure data products meet quality standards across pipelines and platforms. You will implement tests, monitor metrics, and work with data scientists, engineers, and business users to sustain reliable data delivery.

The role emphasizes automation, governance, and collaboration with executives and centers of excellence to optimize data assets and enable strategic decision-making across client environments.