Senior Quality Engineer

Job Title:
Quality Engineer – BDD Implementation (Data Ingestion & Pipeline)

Location:
New York City, NY/Fort Mill, SC

Mode: (Hybrid- 2-3 days)

Experience: 10+ years

Duration:
Full time

We are seeking a skilled Quality Engineer with hands-on experience in Behavior-Driven Development (BDD) to ensure the quality and reliability of our data ingestion and pipeline solutions. The ideal candidate will collaborate with cross-functional teams to define, implement, and automate BDD test scenarios for complex data workflows.

• Collaborate with product owners, data engineers, and business analysts to define acceptance criteria and BDD scenarios for data ingestion and pipeline processes.
• Design, develop, and maintain automated BDD test suites using frameworks such as Behave, Cucumber, pytest-bdd and Playwright for Ui validations.
• Validate data integrity, transformation logic, and end-to-end data flow from source to target systems.
• Identify, document, and track defects; work with development teams to resolve issues.
• Integrate automated tests into CI/CD pipelines for continuous quality assurance.
• Analyze test results, generate reports, and communicate findings to stakeholders.
• Contribute to test data management and environment setup for data pipeline testing.
• Stay current with industry best practices in data quality, test automation, and BDD methodologies.

• Bachelor’s degree in Computer Science, Engineering, or related field.
• 5+ years of experience in software quality assurance or test automation, preferably in data engineering environments.
• Strong experience with BDD frameworks (Behave, Cucumber, pytest-bdd, Playwright) and Gherkin syntax.
• Experience with Implementing Test Runners such as TestNG, Selenium Web Driver to run tests and document reporting and results.
• Proficiency in Python, Java or another programming language used for test automation.
• Solid understanding of ETL/ELT processes, data ingestion, and data pipeline architectures.
• Experience testing data transformations, data quality, and data integrity.
• Familiarity with relational databases (SQL), data warehouses, and cloud data platforms (e.g., AWS Glue) and Snowflake.
• Experience with CI/CD tools (e.g., Jenkins, Git Hub Actions).
• Excellent analytical, problem-solving, and communication skills.

• Knowledge of data governance and data privacy best practices.

Exposure to containerization (Docker, Kubernetes) and infrastructure as code.