Who
are we
Fulcrum Digital is an agile and next-generation
digital accelerating company providing digital transformation and technology
services right from ideation to implementation. These services have
applicability across a variety of industries, including banking & financial
services, insurance, retail, higher education, food, healthcare, and
manufacturing.
Requirements
Role Overview
We are seeking a detail-oriented and highly motivated Senior QA Engineer with strong experience in
PySpark
, cloud technologies, and core QA engineering practices. The ideal candidate will be responsible for ensuring the quality, reliability, and performance of large-scale data and application platforms through comprehensive testing strategies and automation.
This role requires collaboration with developers, data engineers, product teams, and DevOps teams to establish and maintain high-quality engineering standards across cloud-based platforms and data processing systems.
Key Responsibilities
-
Design, develop, and execute comprehensive test plans, test cases, and test strategies.
-
Validate large-scale data pipelines and data transformations built using
PySpark
.
-
Perform functional, regression, integration, API, and end-to-end testing.
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Develop and maintain automated test frameworks and scripts.
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Validate data quality, integrity, completeness, and consistency across systems.
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Work closely with engineering teams to identify, reproduce, and resolve defects.
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Test cloud-native applications and distributed data platforms.
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Participate in CI/CD processes and support automated quality gates.
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Ensure adherence to QA standards, best practices, and release processes.
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Contribute to performance, scalability, and reliability testing initiatives.
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Mentor junior QA engineers and promote quality engineering culture.
Required Skills & Qualifications
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Bachelor’s degree in Computer Science, Engineering, or related field.
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5+ years of experience in Software QA / Quality Engineering.
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Strong understanding of
fundamental QA concepts and methodologies
, including:
-
Test planning and execution
-
Defect lifecycle management
-
Regression and integration testing
-
Test automation
-
SDLC/STLC processes
-
Hands-on experience with:
-
PySpark
-
Cloud platforms (
AWS
, Azure, or GCP)
-
Experience testing data engineering or big data applications.
-
Strong SQL skills and experience validating large datasets.
-
Experience with API testing tools such as Postman or REST Assured.
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Familiarity with automation frameworks using Python, Java, or similar languages.
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Experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
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Strong analytical, debugging, and troubleshooting skills.
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Excellent communication and collaboration abilities.
Preferred Qualifications
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Experience with Databricks or Spark-based platforms.
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Knowledge of data warehouse and ETL testing methodologies.
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Experience with test automation frameworks like Selenium or PyTest.
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Exposure to containerization technologies such as Docker and Kubernetes.
-
Understanding of Agile/Scrum methodologies.
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Cloud certifications are a plus.
Key Competencies
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Quality-first mindset
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Strong attention to detail
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Problem-solving and analytical thinking
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Collaboration and teamwork
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Ownership and accountability
Nice to Have
-
Experience with performance or load testing tools
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Exposure to real-time data streaming systems
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Knowledge of data governance and data validation frameworks
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Experience in enterprise-scale environments
