Senior AI-Powered Quality Assurance Engineer at ParvixCloud · Remote only · 5 - 8 years · ₹6L - ₹9L / yr · Bootstrapped · Remote only · Posted 19 Jun 2026

Key Responsibilities:
✅ Design and implement AI-powered QA strategies, including predictive quality analytics, automated test generation, and intelligent defect prediction.
✅ Build advanced automation frameworks with self-healing scripts, intelligent test prioritization, and adaptive test coverage analysis.
✅ Develop AI-driven quality dashboards, reporting systems, and actionable quality insights.
✅ Drive Agile, DevOps, CI/CD, and Continuous Testing practices in AI-enhanced development environments.
✅ Streamline QA processes to improve release velocity while maintaining high-quality standards.
✅ Collaborate closely with Development, Product, and Operations teams across the SDLC.
✅ Lead innovation initiatives around AI-powered testing tools and emerging QA technologies.
✅ Mentor QA engineers on intelligent automation frameworks and modern quality engineering practices
Required Skills:
🔹 Hands-on experience with AI-powered testing platforms such as *Testim, Mabl, Applitools, Functionize*, or similar tools.
🔹 Strong expertise in *Selenium, Cypress, Playwright, and Appium*.
🔹 Experience with *CI/CD pipelines, DevOps practices, containerization, and cloud-native testing*.
🔹 Proficiency in *Python, Java, or JavaScript/TypeScript*.
🔹 5+ years of QA experience with at least 2+ years in a leadership role.
🔹 3+ years of hands-on experience with AI-driven testing tools and methodologies.
🔹 Experience leading QA transformation, automation strategy, and innovation initiatives.
🔹 Strong analytical, problem-solving, communication, and stakeholder management skills.
Good to Have:
⭐ Predictive analytics and AI-assisted defect management.
⭐ Cloud platforms and enterprise-scale testing ecosystems.
⭐ Performance, Security, and API Automation Testing.
⭐ Experience in Digital Transformation or Enterprise Modernization programs.
⭐ Passion for emerging AI technologies and continuous improvement

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About the team
SecurITe’s mission is to build an Agentic‑AI driven security platform that protects critical infrastructure from modern cyber threats. Our focus is on delivering highly performant, resilient, and intelligent network security systems that help defenders stay ahead of adversaries.
About the Role
We’re looking for a seasoned Senior Quality Engineer to provide technical leadership and architectural oversight for our next‑generation cybersecurity AI platform. In this high-impact role, you will define the technical strategy for quality assurance, ensuring our agentic AI transforms cyber defense with unparalleled reliability.
You will be responsible for the end-to-end quality lifecycle, from architectural reviews to the deployment of scalable automation frameworks. Beyond technical execution, you will serve as a mentor to junior team members, fostering a culture of technical excellence and driving the strategy that ensures our solutions meet the rigorous demands of critical infrastructure protection.
What You’ll Do
● Defining and driving comprehensive QA strategies and roadmaps for the cybersecurity platform.
● Designing, developing, and executing test plans, test cases, and automated scripts to ensure software quality.
● Performing functional, regression, performance, scalability and security testing to identify bugs or defects.
● Collaborating with developers, product managers, and other stakeholders to understand product requirements and testing needs.
● Identifying, documenting, and tracking software defects, ensuring clear communication of issues and their resolutions.
● Leading deep-dive root-cause analysis for critical system defects and security vulnerabilities.
● Conducting thorough reviews of product specifications and software design to identify potential areas of concern before testing.
● Architecting and designing complex, scalable test automation frameworks to optimize CI/CD velocity.
● Ensuring the software meets customer and business requirements by validating the functionality and performance.
● Assisting in continuously improving QA processes, tools, and best practices to enhance software testing efficiency and effectiveness.
● Supporting user acceptance testing (UAT) and assisting clients with product validation.
● Mentoring junior and mid-level engineers, providing technical guidance and conducting architectural reviews.
Required Experience
● A Bachelor’s degree in Computer Science, Information Technology, Computer Engineering, or a related field.
● 8-10 years of proven experience in quality engineering, specifically within network cybersecurity, Identity Providers, or AI-integrated platforms.
● Expertise in manual and automated testing.
● Deep domain expertise in complex system validation and advanced automation practices at scale.
● Proficiency in programming languages like Python to build and run automated test scripts.
● "Strong knowledge of software testing methodologies, performance testing tools (e.g., JMeter, k6), and security traffic generation/simulation tools (e.g., Ixia BreakingPoint, Scapy, or Snort/Suricata traffic generators)."
● Understanding of continuous integration/continuous deployment (CI/CD) pipelines and version control systems like Git.
● Strong communication skills for documenting test results and interacting with cross-functional teams.
● Excellent analytical skills, attention to detail, and problem-solving ability.
● Ability to work independently as well as collaboratively in a team environment.
● A curious mindset with a willingness to quickly learn new technologies and testing tools.
Required Skills & Qualifications
● Familiarity with cloud-based testing environments (GCP, AWS, Azure).
● Experience with cybersecurity products or cloud services or IDP or Web UI
The Mindset
● Problem Solver: You thrive on complex, ambiguous challenges and engineer elegant solutions.
● Ownership‑Driven: You take initiative, move fast, and deliver outcomes without hand‑holding.
● Continuous Learner: You stay ahead of the curve in AI, ML, and emerging technologies.
● Startup DNA: You excel in fast‑moving environments where priorities evolve and impact is immediate.
Strong Senior QA/SDET Profile with hands-on automation building and QA-function ownership
2
Mandatory (Experience 1): Must have 6+ years in QA/test automation/SDET roles with clear progression in scope (Engineer to Senior to Lead)in a B2B SaaS product company
3
Mandatory (Experience 2): Must have direct experience scaling a QA function at a SaaS company and building automation frameworks or QA processes from scratch
4
Mandatory (Tech skill 1): Must have hands-on UI automation experience with Selenium (Java + TestNG) or Playwright / Cypress (JavaScript / TypeScript) using maintainable design patterns like Page Object Model
5
Mandatory (Tech skill 2): Must have API testing & automation experience with Postman and RestAssured (or equivalent) for functional, integration, and contract testing
6
Mandatory (Tech skill 3): Must have experience with CI/CD integration (Jenkins or GitHub Actions) and Git for version control
7
Mandatory (Skill 1): Must have a strong grasp of Agile / Scrum delivery and JIRA for defect and test management
8
Mandatory (Skill 2): Must have experience leading or mentoring QA engineers and collaborating cross-functionally with developers and product teams
9
Mandatory (Skill 3): Must have solid experience using AI in test automation and manual testing exposure
10
Mandatory (Communication): Must have strong communication skills for cross-functional collaboration
11
Mandatory (Company): Must come from a B2B SaaS
The Senior Quality Assurance Analyst will lead a team of Quality Analysts assigned to a project and will be responsible for coordinating all testing efforts. The Senior Quality Assurance Analyst will create and execute test plans and test cases to ensure adherence with specified requirements. The Senior Quality Assurance Analyst will perform functional, regression, integration, and system testing using a combination of manual testing and automated tools to validate end to end system performance. The Senior Quality Assurance Analyst supports external clients through their testing cycles by providing detailed release notes with every delivery, triaging issues reported, and engaging clients to review system discrepancies as needed. The Senior Quality Assurance Analyst will provide training t
Responsibilities:
- Review requirement documentation to ensure understanding of the scope of the project and what needs to be tested.
- Create and maintain test plans and test cases designed to offer adequate test coverage and minimize escaped defects.
- Create and maintain Quality Assurance matrices of test coverage, slippage ratios, and other pertinent quality metrics.
- Follow established quality control processes, test execution methods and standards to identify, analyze, and document issues, bugs, defects, and other problems.
- Complete full regression testing and analyze test results.
- Manage code and data migrations across multiple testing and production environments.
- Perform a thorough shakeout testing after builds/installs are complete.
- Monitor defect tracking system daily and collaborate with the development team to ensure that any defects are fixed in a timely fashion.
- Actively participate in team meetings such as stand-up meetings and sprint retrospectives and provide testing status reporting on a regular basis.
- Provide mentorship and ongoing support to other Quality Assurance resources.
- Develop and document training materials and job aids aimed at fostering more efficient and consistent practices across implementations.
- Evaluate existing practices, identify, and implement process improvement initiatives.
- Take ownership of all functional areas and features on assigned client implementations.
- Reinforce the use of best practices on the team and motivate the team to be more productive.
- Assist with recruitment and onboarding of new hires.
- Lead team of 2-3 Quality Assurance resources and coordinate all testing activities on assigned projects.
- Develop, execute, and maintain automated test scripts using tools such as Katalon, Playwright, or Selenium (Java), ensuring reliable and scalable test coverage.
- Utilize Git branching strategies and CI/CD concepts to integrate automated test execution into build and deployment pipelines, supporting continuous quality validation.
- Leverage AI-powered testing tools and automation frameworks to improve test design, test data generation, defect analysis, and overall testing efficiency while reducing maintenance effort.
- Leverage AI-powered tools to support manual testing activities, including test case generation, exploratory testing, requirement analysis, test data creation, and defect investigation to improve test effectiveness and productivity.
Job Role: Senior QA Engineer
Company: Appmaker by StarApps
Location: Kochi, Kerala (On-Site)
Experience: 3–5 Years
Employment Type: Full-time
About Appmaker by StarApps
At StarApps, we build tools like Appmaker that help thousands of global e-commerce merchants turn their web stores into native mobile apps.
About the Role
We're looking for an experienced QA Engineer to take overall ownership of our QA cycle. You'll do hands-on testing, build strong quality control so fewer issues reach QA in the first place, and
guide our current QA team. Your goal: catch issues early, reduce the number of QA cycles per release, and ship high-quality apps faster.
Key Responsibilities
- QA Ownership: Own the end-to-end QA cycle, from requirement review to final releasesign-off.
- Quality Control: Set up quality checks, entry/exit criteria and checklists that stop issues early and reduce repeat QA cycles.
- Team Guidance: Mentor and guide the current QA team, review their test cases and bug reports, and raise the team's testing standards.
- Test Planning: Create test plans and test cases from the requirements and designs shared, covering functional, regression and edge cases.
- Device & Design Parity Testing: Test on real Android and iOS devices, and run design parity checks against approved designs.
- Bug Management: Report, prioritise and track bugs, document regressed bugs, and verify fixes with the dev team.
- Process Improvement: Find the root causes of recurring bugs and improve QA processes, tools and documentation.
- Communication: Keep management updated on release quality, risks and issues found.
- AI-Assisted Testing: Use AI tools to generate test cases and speed up testing, while reviewing the output carefully.
What We're Looking For
- Experience: 3–5 years in software QA, with strong experience testing mobile apps.
- Ownership: Proven experience owning QA for releases and reducing QA cycles or bug
- leakage.
- Leadership: Experience guiding or mentoring junior QA engineers.
- Testing Expertise: Strong knowledge of test planning, functional, regression,
- smoke/sanity testing and the bug life cycle.
- QA Tools: Hands-on experience with QA tools like BrowserStack, Appium and bug
- trackers such as Jira, and the judgment to pick the right tool for the job.
- AI Tools: Experience or strong interest in using AI tools for testing.
- Attention to Detail: You notice when a price, image, spacing or button looks off.
- Communication: Clear written and spoken English for reports, updates and working with developers and management.
Bonus Points
- Experience testing Shopify or e-commerce apps.
- Experience with test automation (Appium, Playwright or similar) or API testing (e.g.
- Postman).
- Experience setting up QA processes from scratch in a fast-moving team.
Why Join Us?
- Real Impact: Own the quality of apps used by thousands of global brands and millions of shoppers.
- Leadership: Shape how QA works at Appmaker and grow the QA team.
- Modern QA: Work with AI-driven testing tools and a modern workflow.
- Growth & Culture: High ownership and a supportive team in our Kochi office.
Principal Software Engineer
Location: Bangalore India
Department: AI Engineering / Quality Assurance
Experience Level: Mid to Senior
We are looking for a highly motivated Senior AI Test / Automation Engineer to design and scale automated validation frameworks for AI/ML models, LLM-based applications, and agentic systems. This role is critical to ensure that AI solutions meet enterprise standards for quality, reliability, safety, and compliance before and after production deployment.
Key Responsibilities
- Build and maintain AI test automation frameworks for pre-qualification and continuous validation of models and agent workflows
- Develop comprehensive test suites, including:
- Unit, integration, and end-to-end (E2E)
- Functional, regression, performance, and safety testing
- Validate AI system behavior, including:
- Non-deterministic LLM outputs
- Hallucinations and edge cases
- Multi-step agent decision-making
- Design and manage evaluation systems:
- Golden datasets
- Benchmarking pipelines (accuracy, latency, reliability)
- Automate testing within CI/CD pipelines for model updates, prompt changes, and tool integrations
- Implement observability and telemetry to enable traceability, monitoring, and audit readiness
- Collaborate cross-functionally with ML, MLOps, Product, and Security teams to define quality gates and release criteria
- Track and report quality KPIs, including test coverage, defect leakage, and system reliability
- Drive root-cause analysis and continuous improvement across the AI testing lifecycle
Required Skills
Core Engineering
- Strong programming skills in Python; familiarity with Bash, TypeScript, or Go
- Experience with test automation frameworks such as PyTest, Playwright, Selenium, or Cypress
- Proficiency in CI/CD tools (GitHub Actions, Jenkins, GitLab CI)
- Experience with cloud platforms (AWS, Azure, GCP) and containers (Docker, Kubernetes)
AI / ML & Agentic Systems
- Hands-on experience with LLM ecosystems (OpenAI, Anthropic, Bedrock)
- Familiarity with:
- RAG architectures and vector databases (Pinecone, Weaviate)
- Agent frameworks (LangChain, LlamaIndex, AutoGen)
AI Testing Techniques
- Experience with non-deterministic testing approaches (statistical assertions, tolerance thresholds)
- Knowledge of evaluation methods:
- LLM-as-a-judge
- BLEU, ROUGE, semantic similarity scoring
- Experience with prompt and agent regression testing
- Understanding of AI safety testing, including adversarial testing, bias/fairness validation, and jailbreak detection
Tooling (Preferred)
- AI testing & observability tools: LangSmith, TruLens, Arize, Weights & Biases
- Evaluation tools: DeepEval, Ragas, PromptFoo, Giskard
- Monitoring: Prometheus, Grafana, OpenTelemetry
Soft Skills
- Strong analytical and problem-solving skills
- Excellent communication and cross-functional collaboration
- Data-driven mindset with focus on quality KPIs
- Detail-oriented with a strong bias toward automation and scalability
Experience Requirements
- 7+ years in QA, SDET, or test automation engineering
- Proven experience building and scaling automation frameworks
- Hands-on experience with AI/ML systems or LLM-based applications
- Experience testing RAG pipelines or agentic workflows
- Owned end-to-end AI test strategy and architecture
- Defined quality metrics and release gates
- Delivered scalable validation pipelines for production AI systems
- Supported audit and compliance readiness
Preferred
- Experience in enterprise or regulated environments (SOC2, ISO 27001, etc.)
- Exposure to:
- Shift-left testing practices
- Production observability and monitoring
- Chaos or resilience testing
Senior-Level Differentiators
Education
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field
Nice-to-have:
- ISTQB certification
- Cloud/ML certifications (AWS, Azure, GCP)
- AI testing certifications
What Success Looks Like
- AI systems that are accurate, reliable, and safe
- Fully automated test pipelines integrated into CI/CD
- Measurable improvements in defect leakage and model quality
- Strong observability and auditability across AI systems
- Scalable validation frameworks supporting rapid AI innovation
About the role
We need a senior QA professional to assess our current QA practices, set up the right processes, and guide junior team members on execution. You will then scale the practice with Playwright automation.
Responsibilities
Assess existing QA processes, tools and coverage; identify gaps and drive an improvement roadmap.
Define test strategy, QA processes and quality metrics (coverage, defect leakage, release sign-off).
Guide and mentor junior QA engineers on test design, execution and automation.
Build a scalable Playwright (TypeScript) framework for UI and API tests.
Integrate automation into CI/CD with quality gates and clear reporting.
Drive adoption of AI in testing: agentic AI for test generation, self-healing scripts and failure triage, using Playwright MCP and similar tools.
Define QA approaches for AI-powered features, including LLM output evaluation and agent workflow testing.
Partner with dev and product teams to make quality a shared responsibility.
Must have
8–10 years in QA, 4+ years in test automation.
2+ years hands-on Playwright with TypeScript/JavaScript.
Proven experience assessing and setting up a QA practice from scratch.
Strong API testing, CI/CD (GitHub Actions, Jenkins or similar) and Git skills.
Experience leading and coaching junior QA engineers.
Hands-on use of AI coding assistants and agentic AI tools (e.g. Playwright MCP, Claude, GitHub Copilot) in QA workflows.
Good to have
Selenium/Cypress to Playwright migration experience.
Performance, accessibility or visual testing exposure.
ISTQB or equivalent certification.
Experience building or testing MCP servers, AI agents or LLM-based applications (evals, prompt and guardrail testing).
Designation: Test Lead
Location: Hyderabad_Skyview
Job Summary: We are seeking a highly skilled and motivated SDET with strong Java testing expertise and AI engineering exposure to join our dynamic team in Hyderabad. The ideal candidate will have a strong background in software testing with 5+ years of experience, with a focus on automation testing using Selenium and Java. As a Test Lead, you will be responsible for leading testing efforts, ensuring the quality of our software products, and mentoring junior team members. Your expertise in software development and testing methodologies will be crucial in driving our testing strategy and improving our processes.
Responsibilities:
- Lead the software testing efforts for various projects, ensuring high-quality deliverables.
- Design, develop, and execute automated test scripts using Selenium with Java.
- Collaborate with development teams to understand requirements and provide feedback on testability.
- Mentor and guide junior testers in best practices for software testing and automation.
- Develop and maintain test plans, test cases, and test data.
- Identify, document, and track defects using appropriate tools.
- Participate in code reviews and provide input on testing strategies.
- Continuously improve testing processes and methodologies to enhance efficiency.
- Report testing progress and results to stakeholders, ensuring transparency and accountability.
- Stay updated with the latest industry trends and technologies in software testing.
Mandatory Skills:
- Proficiency in Selenium with Java for automated testing.
- Strong understanding of software testing methodologies and best practices.
- Experience in developing and executing test plans and test cases.
- Familiarity with defect tracking tools and test management software.
- Excellent analytical and problem-solving skills.
- Strong communication and interpersonal skills.
- Experience using AI tools for development and testing automation.
- Exposure to AI testing frameworks is preferred.
- Experience in creating test data and performing end to end testing.
Preferred Skills:
- Experience with performance testing tools.
- Knowledge of continuous integration and continuous deployment (CI/CD) processes.
- Familiarity with Agile methodologies.
- Experience in API testing and tools like Postman or SoapUI.
- Understanding of database testing and SQL.
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field.
- Relevant certifications in software testing (e.g., ISTQB) are a plus.
- Proven track record of leading testing efforts in a software development environment.
Senior QA Engineer
Make quality part of the engineering system.
AbleCredit builds software for complex enterprise workflows where AI, APIs, business rules, human decisions, and real-world operations have to work together reliably. We care about building products that work in production - not just in demos. We're looking for a senior quality engineer who can move quality upstream: from release-time testing to better automation, contracts, observability, and engineering practices.
What You'll Own?
• Own quality strategy across web, mobile, backend APIs, integrations, and end-to-end workflows.
• Design and maintain automated regression suites for critical customer journeys.
• Build API, integration, contract, and workflow tests that catch failures before production.
• Partner with engineering and product teams during design - not only after development is complete.
• Define release readiness, risk-based testing, and production validation practices.
• Investigate escaped defects, identify systemic causes, and drive preventive improvements.
• Improve test data, environments, tooling, and CI integration so teams can ship confidently.
What We're Looking For?
• 5+ years in software quality engineering or test automation.
• Strong API and backend testing experience, including asynchronous and integration-heavy systems.
• Experience testing mobile and web applications and understanding client/ server failure modes.
• Ability to write automation in JavaScript/ TypeScript, Python, Java, or a similar language.
• Strong debugging skills across logs, network requests, databases, and distributed services.
• Experience with CI/CD and integrating automated tests into release pipelines.
• A product mindset: prioritize risk and customer impact rather than maximizing test-case counts.
Nice to Have
• Performance, load, security, or reliability testing.
• Experience with Playwright, Cypress, Appium, Postman/ Newman, k6, or similar tooling.
• Experience with event-driven systems, queues, webhooks, and long running workflows.
• Experience testing AI-assisted or non-deterministic product behavior.
How We Think About Quality?
Quality is an engineering responsibility. Automation should create confidence, not dashboards. A production escape should improve the system that allowed it to happen. The goal is simple: ship quickly without making customers our test environment.
Senior Automation Testing Engineer
Location: Bengaluru / Gurugram – Onsite
Experience: 5–11 Years
Employment Type: Full-Time
Key Responsibilities
- Develop and maintain automation test frameworks and scripts.
- Perform both manual and automation testing, including exploratory, functional, regression, and bug verification.
- Develop test cases and contribute to test planning, estimation, and Agile ceremonies.
- Perform non-functional testing for accuracy, reliability, and performance.
- Drive QA process and automation improvements.
Required Skills
- BE/B.Tech/ME/M.Tech in CS/ECE/EE or related field.
- 5–11 years of software testing experience.
- Strong hands-on experience with Python/Java, Selenium, Cucumber, and PyTest.
- Good knowledge of SDLC, testing methodologies, defect lifecycle, and risk assessment.
- Experience with version control and bug-tracking tools.
Good to Have: Linux, Qt/QML, Squish, ISTQB/CSM/PSM, and regulatory/compliance standards.
Senior Quality Engineer
Notice Period: Immediate
Purpose of the Job:
We are seeking a highly skilled and experienced Senior Quality Engineer to join our Enterprise Technology and Data team. This role is crucial in ensuring the delivery of high-quality data-driven solutions and applications across our enterprise systems. The ideal candidate will have deep expertise in quality engineering, automated testing, and extensive experience in testing large-scale data systems, particularly in ETL processes and working with Azure Fabric and Google Cloud data platforms such as BigQuery and Google Cloud Data Pipelines.
As a Senior Quality Engineer, you will be responsible for defining and implementing quality assurance processes, developing automated tests, identifying and mitigating risks, and ensuring the overall quality of our technology and data platforms across multi-cloud environments (Azure and Google Cloud Platform). You will work closely with cross-functional teams including developers, data engineers, and product managers to ensure that the highest standards of quality are maintained throughout the software development lifecycle.
Main Activities:
- · Test Planning & Execution: Design detailed test strategies/plans, test cases, and test scripts to validate data accuracy, integrity, and system functionality in ETL pipelines across Azure and GCP (e.g., Dataflow, Data Fusion, BigQuery pipelines), including both functional and non-functional testing.
- · Data Quality: Collaborate with data engineers to monitor and ensure the accuracy, completeness, and consistency of data across various data platforms including Azure Synapse/Fabric and Google BigQuery, validating transformations and data integrity in ETL pipelines.
- · Data Pipeline Testing: Collaborate with data engineering teams to design and execute tests for Data pipelines running on Azure Fabric as well as Google Cloud services such as Dataflow, Dataproc, and Pub/Sub-based pipelines, ensuring transformation, integration, and storage processes function as expected.
- · SQL Database Testing: SQL Database Testing: Development and execution of SQL-based automated tests for database validation, ensuring data integrity, performance, and security across multiple databases including BigQuery datasets and Azure SQL/Synapse environments.
- · Performance Testing: Conduct performance testing to evaluate the scalability, stability, and performance of large-scale data systems across distributed cloud platforms including Azure and GCP.
- · Automated Testing: Develop and maintain automated test frameworks for data applications, including ETL processes, APIs, and data integration systems using industry-standard tools, and extend automation to support BigQuery validation, GCP pipeline testing, and AI/ML data validation scenarios.
- · Defect Tracking & Resolution: Work with development and operations teams to identify, report, and track defects across multi-cloud data ecosystems, ensuring timely resolution.
- · Continuous Improvement: Propose and implement improvements to testing processes and frameworks to increase efficiency and effectiveness of quality assurance efforts across Azure and Google Cloud-based data platforms and AI-enabled data solutions.
- · Collaboration: Partner with business stakeholders, project managers, and technical teams to ensure alignment with quality goals and deliverables across enterprise data platforms spanning multiple cloud providers.
- · Mentorship: Provide guidance and mentorship to junior quality engineers, helping them improve their technical skills in modern data testing practices including cloud-native and AI-driven validation techniques.
- · Compliance & Best Practices: Ensure adherence to industry standards and best practices related to software quality, particularly in relation to data systems, ETL processes, and cloud technologies including Azure and Google Cloud Platform environments.
Knowledge/Skill Requirements:
· Education:
- o Bachelor’s degree in computer science, Information Technology, Engineering, or a related field.
- · Experience:
- o 5+ years of experience in software quality engineering, with at least 3 years of experience in an enterprise data environment.
- o Proven experience in automated testing tools (e.g., Selenium, JUnit, TestNG, or similar frameworks).
- o Hands-on experience with data validation, transformation, and data pipeline testing in cloud environments, specifically Azure and/or Google Cloud Platform (GCP).
- o Strong understanding of data management, data warehousing, ETL processes, and data integration.
- o Experience with data warehousing, data lakes, and cloud-based ETL tools including Azure Data Factory, Azure Synapse, Google BigQuery, Dataflow, and Dataproc is a plus.
Technical Skills:
- o Proficient in scripting languages (e.g., Python, Java, SQL) for test automation and ETL process validation.
- o Experience working with Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, as well as Google Cloud services such as BigQuery, Dataflow and Cloud Composer (Airflow) for data pipeline orchestration and validation.
- o Strong knowledge of software development methodologies (Agile, Scrum, Waterfall) and experience in a continuous integration/continuous deployment (CI/CD) environment.
- o Familiarity with version control systems (e.g., Git), CI/CD tools (e.g., Jenkins, Azure DevOps), and cloud infrastructure (e.g., Azure, GCP).
- · Soft Skills:
- o Strong analytical, problem-solving, and troubleshooting skills.
- o Excellent communication skills, with the ability to collaborate effectively across departments.
- o Detail-oriented with a passion for ensuring high-quality standards in data-driven solutions.
- o Ability to work independently and as part of a team, managing multiple priorities in a fast-paced environment.
- · Certifications/Additional Training – Nice-to-Have:
- o Relevant certifications (e.g., Azure DevOps, Azure ML, ISTQB, Google Cloud Professional Data Engineer or Professional Cloud Developer) are a plus.
- o Experience working with data governance tools such as Azure Purview and ensuring data compliance












