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Data Quality Engineer - Python/ETL

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Onsite

Data Quality Engineer - Python/ETL

Forward Eye Technologies

Data Quality Engineer - Python/ETL

Skills

Google Cloud PlatformSQL QueriesBig DataPythonDatabricksAWSPySparkAzure

2 months ago

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Important information


Contract type:

Permanent

Location:

Noida, Uttar Pradesh, India

Work mode:

Onsite

Published on:

21 August 2026

What they need


We are seeking a skilled and experienced Data Quality Engineer (Data QE) to join our team. The ideal candidate will have a strong background in Quality Engineering, ETL and database testing, and hands-on expertise with Python, PySpark, SQL, and Databricks. You will be responsible for designing and executing tests to ensure the quality and reliability of data pipelines and analytics platforms.

Key Responsibilities :

  • Design and implement end-to-end test strategies for data pipelines and ETL processes.

  • Conduct thorough ETL and database testing to ensure data accuracy, completeness, and consistency.

  • Develop automation frameworks and scripts using Python and PySpark.

  • Perform data validation and integrity checks using advanced SQL queries.

  • Work with big data platforms such as Databricks for testing and validation.

  • Collaborate closely with data engineers, analysts, and product teams to understand data requirements.

  • Identify data quality issues, troubleshoot, and work with stakeholders to resolve them.

  • Document test cases, results, and provide regular status updates.

Mandatory Skills & Experience :

  • 6+ years of experience in Quality Engineering and QE processes.

  • 23 years of hands-on experience in ETL testing and database testing.

  • 23 years of experience with Python and PySpark for data testing and automation.

  • 23 years of experience in writing complex SQL queries for data validation.

  • Experience working with Databricks or similar big data platforms.

Preferred Qualifications :

  • Experience with cloud data platforms (e.g., AWS, Azure, GCP).

  • Familiarity with CI/CD pipelines and test automation tools.

  • Knowledge of data governance and data quality frameworks.

Education : Bachelors or Masters degree in Computer Science, Information Systems, or a related field.

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