Data QA Engineer: Validate ETL & Big Data Pipelines

Apex Systems LLC; Denver (CO); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

Disability insurance

ESPP

401K program

HSA

EAP with counseling

Discount programs

Job summary

Apex Systems LLC is seeking a Data QA Engineer to ensure the quality of data pipelines and analytics outputs in a Denver onsite role. You will validate ETL processes, collaborate with data engineers, and contribute to automated testing frameworks across big data platforms.

Responsibilities include designing test strategies, executing data-focused tests, and mentoring teammates in QA methodologies to improve data reliability and engineering practices.

Qualifications

• Minimum 5 years of QA experience in data environments.
• Experience testing data pipelines, ETL processes and large datasets.
• Strong SQL and data dashboard experience.

Responsibilities

• Design and execute data-focused test strategies for complex pipelines and ETL workflows.
• Contribute to an existing automation framework.
• Work with PySpark, big data, SQL and ETL processes.
• Design parallel, independent test plans.
• Anticipate defects with strategic test planning.
• Partner with development to set quality gates for products.
• Create instrumentation to measure quality pre-release and in production.
• Mentor others and share QA best practices across teams.

Skills

Data pipelines testing

SQL skills

Python scripting

Test automation

Python for testing

QA methodologies

Big data environments

Communication skills

Education

Bachelor's or Master’s in CS/CE or related field

Tools

Databricks

AWS

Job description

Apex Systems LLC is seeking a Data QA Engineer to ensure the quality of data pipelines and analytics outputs in a Denver onsite role. You will validate ETL processes, collaborate with data engineers, and contribute to automated testing frameworks across big data platforms.

Responsibilities include designing test strategies, executing data-focused tests, and mentoring teammates in QA methodologies to improve data reliability and engineering practices.