Senior Quality Engineer - Data

PayU

Mumbai

On-site

INR 1,200,000 - 1,800,000

Full time

12 days ago
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Job summary

PAYU PAYMENTS PRIVATE LIMITED in Mumbai seeks a Sr Quality Engineer - Data to bridge development and testing, focusing on ETL, DW and BI validation across data pipelines.

You will automate test scenarios in Python, write SQL scripts for Oracle/MSSQL/Postgres, and participate in Agile sprints using JIRA. AWS familiarity is a plus and data warehousing expertise is essential.

Qualifications

  • 3–5 years of ETL, DW, and BI testing experience.
  • 1–2 years of test automation scripting (Robot Framework or Python).
  • Solid understanding of Data Warehousing concepts and technologies.
  • Proficiency in SQL (mandatory) and relational DBMS like Oracle, MSSQL, or Postgres.
  • Preferable: Working knowledge of AWS cloud services.
  • Strong analytical skills and attention to detail.
  • Knowledge of Agile methodology and testing tools like JIRA.

Responsibilities

  • Conduct ETL, Data Warehousing (DW), and BI testing to ensure data system robustness.
  • Create and execute comprehensive test cases, including test scripts and test data, focusing on functional operations and user perspectives.
  • Develop and automate test scenarios using Python scripting.
  • Translate functional specifications into effective testing scenarios with stakeholders.
  • Execute SQL scripts for Oracle, MSSQL, or Postgres to ensure data accuracy.
  • Perform requirement analysis to understand testability and quality standards.
  • Collaborate with Agile teams and contribute to QA during sprints.
  • Leverage JIRA to track and manage testing progress.
  • Ensure compliance with testing methodology standards and best practices.

Skills

ETL testing
DW testing
BI testing
Python scripting
Robot Framework
SQL
Agile
JIRA
AWS knowledge

Tools

Oracle
MS SQL Server
PostgreSQL

Job description

PAYU PAYMENTS PRIVATE LIMITED

Role Title: Sr Quality Engineer - Data

Location: Mumbai Preferred/ Bangalore

About the Team

Our Team is a specialized in bridging the gap between development and testing. Unlike traditional QA roles, SDETs have

strong programming skills and contribute to both the development and testing aspects of software products.

About the Role

Quality Assurance is a systematic process that ensures a product or service meets specified requirements and customer expectations. In software development, QA professionals test applications to identify bugs, verify functionality, and ensure the overall quality of the product.

Responsibilities
  • Conduct ETL, Data Warehousing (DW), and Business Intelligence (BI) testing to ensure the robustness of data systems.
  • Create and execute comprehensive test cases, including the creation of test scripts and test data, focusing on functional operations and user perspectives.
  • Develop and automate test scenarios using Python scripting.
  • Work closely with stakeholders to translate functional specifications into effective testing scenarios.
  • Execute SQL scripts for relational databases such as Oracle SQL, MSSQL, or Postgres, ensuring data accuracy and consistency.
  • Perform requirement analysis to understand testability and ensure adherence to quality standards.
  • Collaborate with teams in Agile environments and contribute to quality assurance during sprints.
  • Leverage tools such as JIRA to track and manage testing progress.
  • Ensure compliance with testing methodology standards and best practices.
Required Qualifications
  • 3–5 years of ETL, DW, and BI testing experience.
  • 1–2 years of test automation scripting (preferably with Robot Framework or Python).
  • Solid understanding of Data Warehousing concepts and technologies.
  • Proficiency in SQL (mandatory) and relational database management systems like Oracle, MSSQL, or Postgres.
  • Preferable: Working knowledge of AWS cloud services.
  • Strong analytical skills and attention to detail.
  • Knowledge of Agile methodology and testing tools like JIRA.

Be a part of our dynamic team and ensure the highest level of quality in our data
engineering processes

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