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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Quality Engineer (Data) - **Company:** Capital Technology Group, LLC - **Location:** Boulder, CO, United States (Remote available) - **Experience:** Expert - **Salary:** $75,000.0 - $110,000.0 - **Contract:** Permanent contract - **Skills:** Testing (Software), Agile Methodology, Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Automation of Tests, Microsoft Azure, Big Data, Information Systems, Computer Programming, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Relational Databases, Distributed Computing Environment, Python (Programming Language), Meta-Data Management, Microsoft Office, Systems Development Life Cycle, Regression Testing, E2e Testing, DataOps, Software Deployment, Software Engineering, Software Quality Assurance (SQA), SQL Databases, Technical Data Management Systems, Strategies of Testing, Workflow Management Systems, Google Cloud, Cloud Platform System, Apache Spark, Build Management, Pytest, Data Lakes, Pyspark, Information Technology, Data Lineage, AWS Glue, AWS Data Analytics, Data Pipelines, Amazon Redshift - **Published:** September 22, 2026 - **Apply:** https://www.builtincolorado.com/job/quality-engineer-data/11289894?handler=ApplyRedirect ## About the Role * Passionate about building quality into data and software from the beginning * A detail-oriented problem solver who enjoys identifying risks and improving processes * Comfortable collaborating across data engineering, analytics, and stakeholder teams * Able to balance strategic quality initiatives with hands-on testing responsibilities * A strong communicator who can clearly document findings and advocate for quality improvements, translating technical data issues for non-technical stakeholders * Curious about emerging tools, technologies, and testing best practices * Motivated by mission-driven work and delivering datasets stakeholders can trust, * 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, and identifying, documenting, prioritizing, and tracking software defects * Experience supporting Agile software development teams * Strong analytical, communication, and problem-solving skills, including the ability to investigate data discrepancies, identify root causes, and communicate technical data quality issues clearly to both technical and non-technical stakeholders Nice to Have * Experience testing financial, securities, regulatory, or other highly governed data * Experience with AWS services such as Amazon S3, AWS Glue, Amazon Redshift, and/or Amazon Athena * Experience implementing data quality frameworks or automated data validation platforms * Experience with Pytest or similar Python testing frameworks * Experience with dbt and/or automated testing of SQL-based transformations * Experience with CI/CD pipelines and automated testing within software development workflows * Experience with data lineage, metadata management, and data observability * Experience testing data in data lakes, lakehouses, or data warehouses * Familiarity with schema evolution, schema validation, and detection of schema drift * Experience designing tests for high-volume datasets and distributed processing environments * Experience supporting federal government agencies * Certified Software Tester (CSTE), ISTQB, or similar certification ## Description Develop and implement quality strategies, automated testing frameworks, and validation practices for data pipelines and analytical datasets. Test accuracy, completeness, integrity, schema consistency, business rules, and freshness using Python, PySpark, SQL, Spark, Airflow, and AWS. Investigate data anomalies and pipeline failures, monitor quality metrics, support CI/CD and releases, and collaborate with engineers, analysts, data scientists, and stakeholders to ensure reliable financial and regulatory data., CTG is seeking a Quality Engineer to join a data engineering team, supporting a program that manages financial and regulatory data. This role develops and implements quality assurance strategies, testing methodologies, and automation practices that keep data accurate, complete, consistent, and reliable across modern data pipelines and analytics platforms, combining strong testing and automation skills with data engineering fundamentals and the rigor financial and regulatory data demands. You Will Get To * 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 to protect downstream data consumers. * 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., Validates complex enterprise data processing, transformations, migrations, reconciliations, reporting, business rules, APIs, and event-driven workflows. Develops data validation strategies, automated database validation scripts, migration tests, and reconciliation reports. Partners with data architects and engineers while mentoring junior testers. The role requires advanced SQL, automation, ETL validation, relational data modeling, large-scale migration testing, and Python programming. Top Skills: APIsETLPythonRelational DatabasesSQL Jupiter Intelligence Data Quality Engineer - Contractor Yesterday In-Office or Remote Boulder, CO, USA Mid level Mid level Big Data * Other * Analytics Own data pipeline integrity, validation, monitoring, and reliability for climate-risk products. Design automated data quality frameworks, investigate infrastructure issues, coordinate with external data vendors, validate data for product and financial models, document post-launch processes, and communicate quality risks. Collaborate with Engineering, Product, Solutions, quantitative modeling, and architecture teams during product launches and iterations. Top Skills: Amazon S3AWSDockerGitPandasPostgresPrefectPydanticPytestPythonSnowflakeSQLTemporal Archera Software Engineer 5 Days Ago In-Office or Remote Mid level Mid level Software Build automated validation, reconciliation, anomaly detection, and test automation for cloud billing data across AWS, Azure, and Google Cloud. Investigate and resolve data-quality issues, automate preventive checks, document provider billing models, support customer-facing data questions, and use AI tooling to accelerate investigation and anomaly triage. Top Skills: AirflowArgoAWSCiDagsterDbtETLGCPGreat ExpectationsAzurePythonSodaSQL What you need to know about the Colorado Tech Scene With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation. Key Facts About Colorado Tech * Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey) * Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3 * Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech * Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook) * Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures * Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Let’s Talk Quality!](https://www.wearedevelopers.com/videos/100012-let-s-talk-quality) - [pytest: Simple, rapid and fun testing with Python](https://www.wearedevelopers.com/videos/213-pytest-simple-rapid-and-fun-testing-with-python) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Excellent Software Testing](https://www.wearedevelopers.com/videos/87-excellent-software-testing) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [The 8 Best Code Testing Tools](https://www.wearedevelopers.com/magazine/402-the-8-best-code-testing-tools) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [The 12 Best Jobs for Software Engineers](https://www.wearedevelopers.com/magazine/401-the-12-best-jobs-for-software-engineers) - [Top Characteristics of a Software Engineer](https://www.wearedevelopers.com/magazine/166-top-characteristics-of-a-software-engineer)