Quality Engineer, Data

Capital Technology Group, LLC

. Develop and implement data quality strategies, standards, testing practices, documentation, and maintenance processes for data pipelines and analytical datasets .

Posted 9/21/2026full-timeRemote • United StatesSeniorLead💰 $75,000 - $110,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing data quality strategies, testing practices, and validation processes for data pipelines. Proficient in utilizing programming languages and tools such as Python, SQL, and Apache Spark to ensure data accuracy and integrity throughout the software development lifecycle.

Highest-signal resume keywords

Data Quality PrinciplesPython ProgrammingAutomated Testing FrameworksApache Spark/PySparkAWS Data Services

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Quality StrategiesAutomated TestingSQLETL/ELT ProcessesData Pipeline TestingData Anomaly InvestigationUnit TestingIntegration TestingStatistical ValidityCI/CD

Soft Skills

Analytical SkillsCommunication SkillsProblem-Solving Skills

Tools & Technologies

Apache AirflowAWSAmazon S3Pytest

Industry Keywords

Software Quality AssuranceQuality EngineeringAgile DevelopmentData IntegrityData Completeness

Tech Stack

Tools & technologies

AirflowApacheAWSCloudETLPySparkPythonSDLCSparkSQL

About the role

Key responsibilities & impact

Develop and implement data quality strategies, standards, testing practices, documentation, and maintenance processes for data pipelines and analytical datasets
Design and execute automated and manual tests covering data accuracy, completeness, integrity, uniqueness, schema consistency, business rules, freshness, and statistical validity
Build automated quality checks and integration/end-to-end tests using Python, PySpark/Spark, SQL, and Apache Airflow
Validate data transformations and pipelines across Apache Spark, Python, AWS, Amazon S3, and related AWS data services
Develop reusable testing frameworks and utilities for data pipelines and CI/CD, ensuring code and data are validated before production release
Implement quality validation across raw, cleaned, curated, and analytics-ready data, establishing thresholds, rules, and acceptance criteria
Investigate data anomalies, schema changes, missing data, pipeline failures, and other quality issues; identify root causes and partner with Data Engineers on resolution
Conduct code and product reviews and ensure new pipelines and transformations include appropriate unit, integration, and data quality testing
Monitor data quality metrics and dashboards and support automated regression testing
Collaborate with Data Engineers, Data Scientists, Analysts, and stakeholders to translate business and regulatory requirements into data quality controls throughout the SDLC
Support UAT, release validation, production deployments, and documentation of test strategies, requirements, defects, and validation procedures

Requirements

What you’ll need

Applicants MUST BE US Citizens and be able to obtain Public Trust clearance
Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience)
7+ years of professional experience in software quality assurance, testing, or quality engineering roles
Strong programming experience with Python and experience developing automated tests and test frameworks (e.g., Pytest or comparable)
Strong understanding of data quality principles and methodologies, including accuracy, completeness, consistency, uniqueness, validity, and timeliness
Experience working with relational databases and SQL
Experience testing data pipelines, ETL/ELT processes, or large-scale data transformations
Experience with distributed data processing technologies such as Apache Spark/PySpark
Familiarity with Apache Airflow or another workflow orchestration platform
Experience working with cloud-based data platforms, preferably AWS
Experience creating, executing, and maintaining automated and manual test plans and test cases
Experience identifying, documenting, prioritizing, and tracking software defects
Experience supporting Agile software development teams
Strong analytical, communication, and problem-solving skills
Ability to investigate data discrepancies, identify root causes, and communicate technical data quality issues clearly to technical and non-technical stakeholders

Benefits

Comp & perks

Remote Work (Hybrid roles will be specified in the job post)
Competitive Compensation Package
Medical, Dental, and Vision
Life Insurance, Short/Long Term Disability
Employee Assistance Program
401(k) with 4% matching
Liberal PTO vacation policy
Generous Annual Continuing Education
Annual Wellness Budget
Bonus Incentive Programs (Employee referrals and performance-based rewards)