ETL Tester | Azure Data Engineering | Databricks | SQL

Vrinda International

Bengaluru

On-site

INR 1,500,000 - 2,500,000

Full time

14 days+

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Job summary

Vrinda International is seeking an experienced ETL Tester to join our team in Bengaluru. You will be responsible for end-to-end data and ETL testing, validating data accuracy, and ensuring robust data pipelines using Databricks, SQL, and Python.

The ideal candidate has 4–8 years of hands-on experience, strong SQL skills, and familiarity with Azure Data Engineering concepts. You will work in an Agile/DevOps setting, coordinating with engineers and QA to deliver high-quality analytics solutions.

Qualifications

  • 4–8 years of hands-on ETL testing experience.
  • Strong SQL skills and data validation expertise.
  • Hands-on Databricks/Spark experience with SQL & Python preferred.
  • Understanding of Azure Data Engineering concepts and data pipelines.

Responsibilities

  • Execute end-to-end data and ETL testing across pipelines.
  • Perform integration testing and defect management in Agile/DevOps environments.
  • Collaborate with data engineers and QA to ensure data quality and reliability.

Skills

ETL Testing
SQL
Databricks
Python
Spark

Job description

Welcome to Vrinda International's Talent Portal

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Join thousands of professionals who've advanced their careers through Vrinda International. Create your profile today and let's connect your talent to global opportunities!
Job Description

? Experience: 4–8 Years

? Notice Period: Immediate to 30 Days Preferred

We are looking for an experienced ETL Tester with strong expertise in Data & Analytics Testing, Databricks, SQL, and Azure Data Engineering concepts. The ideal candidate should have hands-on experience in end-to-end testing activities, integration testing, defect management, and Agile/DevOps environments.

Requirements

Required Skills:

  • Strong experience in ETL/Data Testing
  • Advanced SQL knowledge
  • Hands-on experience with Databricks / Spark (SQL & Python preferred)
  • Understanding of Azure Data Engineering concepts:
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