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.
• 
  Develop and maintain automated test frameworks and scripts.
• 
  Validate data quality, integrity, completeness, and consistency across systems.
• 
  Work closely with engineering teams to identify, reproduce, and resolve defects.
• 
  Test cloud-native applications and distributed data platforms.
• 
  Participate in CI/CD processes and support automated quality gates.
• 
  Ensure adherence to QA standards, best practices, and release processes.
• 
  Contribute to performance, scalability, and reliability testing initiatives.
• 
  Mentor junior QA engineers and promote quality engineering culture.

Required Skills & Qualifications

• 
  Bachelor’s degree in Computer Science, Engineering, or related field.
• 
  5+ years of experience in Software QA / Quality Engineering.
• 
  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.
• 
  Familiarity with automation frameworks using Python, Java, or similar languages.
• 
  Experience with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI.
• 
  Strong analytical, debugging, and troubleshooting skills.
• 
  Excellent communication and collaboration abilities.

Preferred Qualifications

• 
  Experience with Databricks or Spark-based platforms.
• 
  Knowledge of data warehouse and ETL testing methodologies.
• 
  Experience with test automation frameworks like Selenium or PyTest.
• 
  Exposure to containerization technologies such as Docker and Kubernetes.
• 
  Understanding of Agile/Scrum methodologies.
• 
  Cloud certifications are a plus.

Key Competencies

• 
  Quality-first mindset
• 
  Strong attention to detail
• 
  Problem-solving and analytical thinking
• 
  Collaboration and teamwork
• 
  Ownership and accountability

Nice to Have

• 
  Experience with performance or load testing tools
• 
  Exposure to real-time data streaming systems
• 
  Knowledge of data governance and data validation frameworks
• 
  Experience in enterprise-scale environments