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Adobe Qa Engineer Jobs (NOW HIRING)

Anika Systems

Quality Assurance Engineer

Leesburg, VA · On-site +1

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 ...

www.wingbrace.com

Quality Assurance Engineer

Lincoln, MA · On-site

Software Quality Assurance Engineer Location -Onsite Hybrid role Lincoln Massachusetts About Wingbrace Wingbrace (www.wingbrace.com) is a software and technical services company focused on the ...

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BWX Technologies

QA Engineer

Barberton, OH

Quality Assurance Engineer - BWX Technologies, Inc. - Barberton, OH Responsibilities include: * Support of production manufacturing processes. * Resolution of quality issues. * Assist in the ...

Redolent, Inc

QA Engineer

Sunnyvale, CA · On-site

Hello, One of our direct client is urgently looking forQA Engineer @ Sunnyvale , CA TITLE: QA Engineer LOCATION: Sunnyvale , CA Duration: 6 to 12+ months Description QE Engineer in this role will ...

THRONE LABS INC

QA Engineer

Los Angeles, CA · Remote

Software Quality Assurance Engineer FULL-TIME, WASHINGTON, D.C. About the job Throne aims to provide peace of mind to those that venture out each day -- making it so no one has to worry about finding ...

THRONE LABS INC

QA Engineer

Washington, DC · Remote

Software Quality Assurance Engineer FULL-TIME, WASHINGTON, D.C. About the job Throne aims to provide peace of mind to those that venture out each day -- making it so no one has to worry about finding ...

THRONE LABS INC

QA Engineer

Washington, DC · Remote

Software Quality Assurance Engineer FULL-TIME, WASHINGTON, D.C. About the job Throne aims to provide peace of mind to those that venture out each day -- making it so no one has to worry about finding ...

MM International

QA Engineer

Redmond, WA · On-site

QA Engineer - Onsite (Redmond, WA) We're hiring a QA Engineer to support Windows security initiatives. This is an onsite role in Redmond , with a strong preference for local candidates (relocation ...

BWX Technologies

QA Engineer

Barberton, OH

Quality Assurance Engineer - BWX Technologies, Inc. - Barberton, OH Responsibilities include: * Support of production manufacturing processes. * Resolution of quality issues. * Assist in the ...

THRONE LABS INC

QA Engineer

Los Angeles, CA · Remote

Software Quality Assurance Engineer FULL-TIME, WASHINGTON, D.C. About the job Throne aims to provide peace of mind to those that venture out each day -- making it so no one has to worry about finding ...

EDAG, Inc.

Quality Assurance Engineer

Farmington, MI · On-site

The Quality Assurance Engineer ensures the product and process quality in the project through analytical and constructive quality assurance measures. * Planning, implementation and tracking of the ...

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EDAG Inc

Quality Assurance Engineer

Farmington, MI · On-site

The Quality Assurance Engineer ensures the product and process quality in the project through analytical and constructive quality assurance measures. * Planning, implementation and tracking of the ...

Moog, Inc.

Quality Assurance Engineer

Buffalo, NY · On-site

$65K - $90K/yr

Quality Assurance Engineer Reporting To: Manager, QA Engrg. Work Schedule: Onsite - Buffalo, NY Moog Military Aircraft Group is looking for a Quality Assurance Engineer to plan, implement, and ...

Cinder LLC

QA Engineer

Sunnyvale, CA · On-site

$60/hr

Title: QA Engineer Pay Rate: $60/hr Location: Sunnyvale, CA Type: Fulltime with benefits About Novus Labs Novus Labs is our sibling company that provides engineering support to the largest tech ...

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Adobe QA Engineer information

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How much do adobe qa engineer jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for adobe qa engineer in the United States is $48.54, according to ZipRecruiter salary data. Most workers in this role earn between $38.22 and $55.53 per hour, depending on experience, location, and employer.

What are some common challenges Adobe QA Engineers face when testing creative software products?

Adobe QA Engineers often encounter challenges related to the complexity and variety of creative software tools, such as ensuring cross-platform compatibility, validating new features, and maintaining testing efficiency as products evolve. Since Adobe products like Photoshop and Illustrator are used by millions of professionals worldwide, QA Engineers must anticipate diverse user scenarios and edge cases. Collaboration with developers, designers, and product managers is key to understanding user expectations and prioritizing critical issues, making strong communication skills essential in this role.

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

To thrive as an Adobe QA Engineer, you need strong knowledge of software testing methodologies, test automation, and a relevant degree in computer science or a related field. Familiarity with tools like Selenium, JIRA, TestNG, and Adobe’s own suite of products is typically required, along with experience in scripting languages such as Java or Python. Attention to detail, analytical thinking, and effective communication are vital soft skills for identifying issues and collaborating with development teams. These skills ensure the delivery of high-quality, bug-free software products that meet Adobe's standards and user expectations.

What is the difference between Adobe Qa Engineer vs Software Tester?

AspectAdobe Qa EngineerSoftware Tester
CredentialsBachelor's in Computer Science or related, QA certificationsBachelor's in Computer Science or related, QA certifications
Work EnvironmentTech companies, software development teams, collaborativeVaried industries, testing labs, development teams
Industry UsageCommon in software and digital media companies like AdobeWidespread across tech, finance, healthcare, and more

Adobe Qa Engineers focus on testing Adobe's software products, often requiring specialized knowledge of Adobe tools and platforms. Software Testers have a broader scope, working across various industries and products. While both roles involve quality assurance, Adobe Qa Engineers typically work within Adobe or similar tech firms, emphasizing automation and product-specific testing.

What does an Adobe QA Engineer do?

An Adobe QA Engineer is responsible for ensuring the quality and functionality of Adobe's software products by designing and executing test plans, identifying bugs, and collaborating with developers to resolve issues. They use a variety of testing methodologies, such as manual and automated testing, to verify that software meets specified requirements and is free of defects. QA Engineers at Adobe also contribute to the improvement of testing processes and tools, helping to deliver high-quality user experiences.
More about Adobe QA Engineer jobs
What job categories do people searching Adobe Qa Engineer jobs look for? The top searched job categories for Adobe Qa Engineer jobs are:
Adobe QA Engineer jobs near you
Infographic showing various Adobe Qa Engineer job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $100,970 per year, or $48.5 per hour.
Quality Assurance Engineer

Quality Assurance Engineer

Anika Systems

Leesburg, VA • On-site, Remote

Full-time

Posted 10 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.

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