Etl Test Engineer

2 days ago

Bengaluru, Karnataka, India Dynpro Full time ₹ 9,00,000 - ₹ 12,00,000 per year

  1. Data Management: Strong understanding of data management principles, Migration projects architecture, Proficiency in working with different types of databases (SQL, NoSQL) and data formats (CSV, JSON, XML).

  2. ETL (Extract, Transform, Load) Testing: Experience with ETL Validation with different sources, validation of transformation of business rules. Knowledge of validation of ETL tools is beneficial.

  3. Programming Skills: Proficiency in programming languages commonly used in data engineering such as Python, Java, or Scala with Spark. Knowledge of scripting languages like Bash or PowerShell can also be useful for automation tasks.

  4. SQL: Strong SQL skills for querying and manipulating data in relational databases. This includes writing complex SQL queries and understanding database indexing.

  5. Testing Principles: Understanding of software testing principles, methodologies (e.g., Agile, Scrum), and best practices. Knowledge of test planning, test case design, and test execution strategies.

  6. Data Visualization: Ability to visualize data effectively using tools like Tableau, Power BI, or matplotlib in Python. This skill helps in presenting test results and insights to stakeholders in a clear and understandable manner.

  7. Automation Tools: Experience with automation tools and frameworks for test data provisioning and management. Familiarity with CI/CD pipelines for automated testing is also valuable, preferrably on Azure DevOps. Knowledge of Azure databricks utilizing python and spark is a must.

  8. Domain Knowledge: Understanding of the retail domain or industry. This helps in designing relevant test scenarios and ensuring data accuracy according to domain-specific requirements.

  9. Communication and Collaboration: Effective communication skills to collaborate with cross-functional teams including developers, QA engineers, and business stakeholders. Ability to articulate technical concepts to non-technical audiences is important.

  10. Problem-Solving Skills: Strong analytical and problem-solving skills to identify data-related issues, troubleshoot them efficiently, and propose effective solutions.

  11. Test Management tools: Working Knowledge of test management tools like JIRA Role & responsibilities

Preferred candidate profile

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