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Qa Engineer Manager Jobs in Virginia (NOW HIRING)

Anika Systems is seeking a highly technical Quality Assurance Engineer with strong development, SQL ... Support enterprise data management programs and OCDO initiatives by ensuring data quality and ...

Job Title: QA Engineer Duration: 6-12 Months Location: Fairfax, VA Description: 8+ Years experience Selenium experience Javascript, Python etc. Telecom experience in needed Thank You, Ashok Kumar ...

Quality Assurance Engineer

Lynchburg, VA · On-site

$85K - $134K/yr

Our joint ventures provide environmental restoration and operations management at a dozen U.S ... As our Quality Assurance (QA) Engineer, you will be responsible for ensuring the quality ...

QA Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this position ... In this role, you will collaborate closely with developers, product managers, and other ...

QA Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this position ... In this role, you will collaborate closely with developers, product managers, and other ...

Our joint ventures provide environmental restoration and operations management at a dozen U.S ... As our Quality Assurance (QA) Engineer, you will be responsible for ensuring the quality ...

Our joint ventures provide environmental restoration and operations management at a dozen U.S ... As our Quality Assurance (QA) Engineer, you will be responsible for ensuring the quality ...

QA Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this position ... In this role, you will collaborate closely with developers, product managers, and other ...

Our flexible, AI-powered content management platform (CMS) enables teams to move faster ... We are looking for a Quality Assurance Engineer who is passionate about delivering high-quality ...

You will collaborate with the rest of the QA Team and developers to execute the quality assurance ... Experience using test management and ALM tools, such as Azure DevOps (formerly VSTS) or OpenText ...

Experience using test management and ALM tools, such as Azure DevOps (formerly VSTS)or OpenText ALM ... Experience performing QA activities in commercial cloud environments, such as Microsoft Azureor ...

Job Title: QA Engineer Company: BLN24 About Us ... We find strength in teamwork-a better you is a better us BLN24 is an award-winning Management ...

Quality Assurance Engineer

Leesburg, VA · On-site

$90K - $110K/yr

As a QA Engineer at Commence, you will serve as the quality gate for our engineering teams, owning ... Support and expand test coverage for document management and OCR-integrated workflows, validating ...

New

BLN24 is seeking a QA Engineer to support the development and maintenance of Adobe Experience Manager (AEM) Forms applications, including customer-facing forms and notice generation systems. This ...

Exostar is seeking a detail-oriented, quality-first QA Engineer who delivers confidence at the same pace our engineering team delivers code. This is not a manual testing or checkbox role. We're ...

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Qa Engineer Manager information

What are the key skills and qualifications needed to thrive as a QA Engineer Manager, and why are they important?

To thrive as a QA Engineer Manager, you need expertise in software testing methodologies, quality assurance processes, and a background in computer science or a related field. Familiarity with automation tools (like Selenium, Jenkins), test management systems, and relevant certifications such as ISTQB are typically required. Strong leadership, communication, and problem-solving skills set outstanding QA Engineer Managers apart. These skills ensure robust quality standards, efficient team management, and the successful delivery of reliable software products.

What does a QA Engineer Manager do?

A QA Engineer Manager oversees the quality assurance processes within a software development team. They are responsible for leading QA engineers, developing testing strategies, and ensuring that products meet quality standards before release. This role involves coordinating with other departments, managing testing schedules, and mentoring team members. Additionally, QA Engineer Managers help to identify process improvements and ensure compliance with industry standards.

How does a QA Engineer Manager typically support the professional development of their QA team members?

A QA Engineer Manager plays a key role in mentoring and guiding team members by providing regular feedback, identifying skill gaps, and facilitating opportunities for learning and growth. This often includes organizing training sessions, encouraging certification pursuits, and supporting participation in industry events. Additionally, QA Engineer Managers may help team members set clear career goals by aligning project assignments with individual aspirations, ensuring a motivating and growth-oriented environment. This approach not only enhances overall team performance but also fosters long-term career advancement for each QA professional.
What are the most commonly searched types of Qa Engineer jobs in Virginia? The most popular types of Qa Engineer jobs in Virginia are:
What are popular job titles related to Qa Engineer Manager jobs in Virginia? For Qa Engineer Manager jobs in Virginia, the most frequently searched job titles are:
Infographic showing various Qa Engineer Manager job openings in Virginia as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.
Quality Assurance Engineer

Quality Assurance Engineer

Anika Systems

Leesburg, VA • On-site, Remote

Full-time

Re-posted 23 days ago


Job description

Anika Systems is seeking a highly technical Quality Assurance Engineer with strong development, SQL, and Python expertise to support enterprise data platforms for federal clients. This is not a traditional manual QA role and this position requires a developer mindset, focused on automation, data validation, and platform reliability across modern cloud-based architectures.
The ideal candidate will design and implement automated testing frameworks for ETL pipelines, Apache Iceberg data architectures, XBRL datasets, and performance-optimized structures such as materialized views-ensuring data accuracy, integrity, and trust across the enterprise. This role also requires proficiency in AI tools and AI-driven workflows, leveraging automation and intelligent testing techniques to improve quality and delivery speed.
This opportunity is 100% remote.
Key Responsibilities
Test Automation & QA Engineering
  • Design, develop, and maintain automated QA frameworks for data pipelines, APIs, and analytics platforms using Python and SQL.
  • Build reusable testing utilities for data validation, regression testing, and pipeline certification.
  • Integrate automated tests into CI/CD pipelines to support continuous testing and deployment.
  • Develop unit, integration, and end-to-end test cases for complex data workflows.
  • Leverage AI-assisted testing tools to generate test cases, identify edge cases, and improve test coverage.
Data Validation & ETL Testing
  • Validate ETL/ELT pipelines to ensure accurate ingestion, transformation, and delivery of data.
  • Create automated checks for data completeness, consistency, accuracy, and timeliness.
  • Test ingestion and transformation of complex datasets, including XBRL financial data.
  • Implement reconciliation and audit mechanisms across source-to-target mappings.
  • Apply AI-driven anomaly detection to identify data quality issues and pipeline failures.
Iceberg & Materialized View Testing
  • Develop and execute test strategies for Apache Iceberg-based data lakehouse architectures, including:
    • Schema evolution validation
    • Time travel and versioning accuracy
    • Partitioning and performance behavior
  • Validate and compare materialized views vs. Iceberg table performance and consistency, including:
    • Query performance benchmarking
    • Data freshness and latency
    • Storage efficiency and maintenance overhead
  • Ensure alignment between precomputed datasets (materialized views) and underlying source data.
Data Quality, Metadata & Context Validation
  • Implement automated validation for data quality rules, lineage, and metadata accuracy.
  • Support context engineering by validating that datasets include proper business context, definitions, and relationships.
  • Integrate QA processes with enterprise data catalogs and metadata systems to ensure discoverability and trust.
  • Validate AI-generated metadata, lineage, and transformations for accuracy and traceability.
AI-Driven Quality Engineering
  • Apply AI/ML and generative AI tools to enhance QA processes, including intelligent test generation, defect prediction, and automated root cause analysis.
  • Validate data readiness for AI/ML and generative AI use cases, ensuring datasets meet quality, completeness, and governance standards.
  • Collaborate with data and AI teams to test data pipelines supporting RAG, analytics, and machine learning workflows.
  • Ensure alignment with responsible AI practices, including traceability, explainability, and data integrity.
OCDO & Data Strategy Support
  • Support enterprise data management programs and OCDO initiatives by ensuring data quality and reliability across systems.
  • Contribute to data maturity assessments by evaluating data quality, testing coverage, and governance adherence.
  • Align QA processes with Federal Data Strategy and Evidence Act requirements.
Stakeholder Collaboration & Agile Delivery
  • Work closely with data engineers, data architects, and analysts to define test strategies and acceptance criteria.
  • Participate in stakeholder engagement sessions and listening campaigns to understand data quality expectations and pain points.
  • Document test results, defects, and quality metrics for both technical and non-technical stakeholders.
  • Operate within Agile teams to iteratively improve data quality processes and tooling.
  • Promote adoption of AI-driven efficiencies and automation across QA and data engineering workflows.
Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
  • 5+ years of experience in QA engineering, data testing, or software development.
  • Strong programming skills in Python and advanced proficiency in SQL.
  • Experience building automated test frameworks for data platforms and ETL pipelines.
  • Hands-on experience with:
    • AWS data services (S3, Glue, Redshift, Lambda, etc.)
    • Apache Iceberg or similar data lake technologies
  • Experience validating materialized views and performance-optimized data structures.
  • Familiarity with XBRL or complex financial/regulatory datasets.
  • Understanding of data modeling, metadata, and data governance principles.
  • Experience with CI/CD tools and automated testing integration.
  • Demonstrated proficiency with AI tools and AI-assisted development/testing workflows.
  • Understanding of data quality requirements for AI/ML and analytics use cases.
  • U.S. Citizenship required; ability to obtain and maintain a federal clearance.
Preferred Qualifications
  • Experience supporting federal agencies such as SEC, DHS, Treasury, or Federal Reserve System.
  • Familiarity with data catalog and governance tools (e.g., Collibra, Alation, ServiceNow).
  • Experience with Apache Spark or distributed data processing frameworks.
  • Knowledge of data quality tools and observability platforms.
  • Exposure to data maturity frameworks (e.g., EDM DCAM, TDWI).
  • Experience testing large-scale cloud data platforms and lakehouse architectures.
  • Experience validating data pipelines supporting AI/ML, analytics, or generative AI solutions.
  • Familiarity with AI-driven testing tools or frameworks.