Note: The job is a remote job and is open to candidates in USA. Capital Technology Group provides consulting services in software development, digital transformation, data analytics and visualization, and cybersecurity. The Quality Engineer will support a data engineering team by developing quality assurance strategies, automated and manual testing, and validation practices to ensure financial and regulatory data is accurate, complete, consistent, and reliable across pipelines and analytics platforms.
Responsibilities
- 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
Skills
- 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, 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
- 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
Benefits
- 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)*
Company Overview