Test Automation Engineer – GE Plant

4 days ago

Vizag, Andhra Pradesh, India Cube Hub Inc. Full time

Job Title: Test Automation Engineer – Data & Analytics

Location: 100% Remote (Nearshore or Offshore with 3–5 hours overlap with CST)

Start Date: Immediate

Max Bill Rate: [As applicable]

Position Overview:

We are seeking a detail-oriented and highly skilled Test Automation Engineer to join our Data & Analytics team. The role focuses on developing Golden Model simulations using Python, creating and validating synthetic test data, and ensuring high-quality data delivery in a CI/CD environment. Candidates must have experience with GE Plant Applications.

Key Responsibilities:

  • Design and develop automated scripts in Python to create a golden model within SQL Server for test automation.
  • Collaborate with developers and analysts to understand data requirements and ensure proper test coverage.
  • Integrate testing into CI/CD pipelines to support continuous delivery and deployment.
  • Identify, document, and track defects and inconsistencies in data.
  • Contribute to test automation strategies and reusable SQL test frameworks.

Required Skills & Qualifications:

  • Strong experience in Test Automation, particularly with data validation and transformation logic.
  • Proficiency in Python, including frameworks such as:
  • YData-Synthetic
  • SDV (Synthetic Data Vault)
  • Gretel-Synthetics
  • SynthCity
  • DoppelGANger
  • Experience in CI/CD environments and integrating automated tests into pipelines.
  • Solid understanding of relational databases and data warehousing concepts.
  • MUST HAVE: Experience with GE Plant Applications.
  • Nice to have: Experience with MS SQL Server.
  • Excellent analytical and problem-solving skills.

Additional Notes:

  • Candidates should be able to articulate SQL tables they have interacted with in GE Plant Applications during interviews.
  • Immediate availability is required; long notice periods are not acceptable.

Skill Priority:

  1. Test Automation with a focus on data validation & transformation logic
  2. Relational databases and data warehousing concepts
  3. Python-based synthetic data frameworks
  4. GE Plant Applications experience

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