Data Quality Engineer — Automation for Pipelines (Remote)

Capital Technology Group; United States; Hybrid; USD 75,000 - 110,000; Full time

Benefits offered by this job

Remote Work

Medical, Dental, Vision

401(k) with matching

PTO and Continuing Education

Wellness budget

Job summary

Capital Technology Group is seeking a Quality Engineer to join a data engineering team, driving data quality across modern pipelines and analytics platforms. You will develop quality assurance strategies, implement automated tests, and collaborate with Data Engineers to ensure accurate, complete, and reliable data in financial and regulatory contexts.

The role combines testing rigor with data engineering fundamentals, requiring strong Python, PySpark, SQL, and Airflow experience, plus the

Qualifications

• Bachelor’s degree in a related field or equivalent experience.
• 7+ years in software quality assurance, testing, or quality engineering.
• Strong Python programming experience and automated test development (Pytest or equivalent).
• Solid data quality principles: accuracy, completeness, consistency, and timeliness.
• Experience with relational databases and SQL.
• Experience testing data pipelines and large-scale data transformations.
• Experience with Spark/PySpark and Airflow; AWS data services.
• Experience building automated tests, CI/CD, and QA frameworks.
• Experience supporting Agile software development teams.
• Strong analytical and communication skills for cross-functional work.

Responsibilities

• Develop and implement data quality strategies, standards, and testing for data pipelines and datasets.
• Design and execute automated and manual tests covering data accuracy, completeness, integrity, and schema rules.
• Build automated quality checks and integration tests using Python, Spark, SQL, and Airflow.
• Validate data transformations across Spark, Python, and AWS data services.
• Develop reusable testing frameworks and CI/CD utilities for data pipelines.
• Establish quality validation across raw to analytics-ready data with thresholds and criteria.
• Investigate data issues and coordinate with Data Engineers for root cause resolution.
• Conduct code and product reviews ensuring unit, integration and data quality tests.
• Monitor data quality metrics and support automated regression testing.
• Collaborate with Data Engineers, Analysts and Stakeholders to translate requirements into data quality controls.

Skills

Python

PyTest

SQL

Airflow

Spark

AWS

Data quality

QA automation

Agile

Communication

Education

Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field

Tools

PyTest

Spark/PySpark

SQL

Airflow

AWS

dbt

Job description

Capital Technology Group is seeking a Quality Engineer to join a data engineering team, driving data quality across modern pipelines and analytics platforms. You will develop quality assurance strategies, implement automated tests, and collaborate with Data Engineers to ensure accurate, complete, and reliable data in financial and regulatory contexts.

The role combines testing rigor with data engineering fundamentals, requiring strong Python, PySpark, SQL, and Airflow experience, plus the