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Data Quality Engineer

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Hybrid

Data Quality Engineer

Epam Systems

Data Quality Engineer

Skills

Google Cloud PlatformSQL QueriesBig DataPythonTesting & QAData AnalysisAWSPySparkHadoopProcess ImprovementAzure

1 month ago

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Important information


Contract type:

Permanent

Salary:

₹2,000,000 – ₹3,500,000 / year

Location:

Gurugram, Haryana, India

Work mode:

Hybrid

Published on:

28 September 2026

What they need


We're hiring an experienced Senior Data Quality Automation Engineer to ensure the accuracy and reliability of our data systems. In this role, you will contribute to developing test scripts, enhancing automated testing frameworks, and collaborating closely with development teams. Your expertise in data models, ETL architecture, and automation testing will drive the quality and integrity of our data-driven solutions.

Responsibilities:

  • As Data Quality Engineer, you are responsible for:
  • Defining Quality Metrics
  • Defining quality standards and metrics for the current project/product. Working with all stake holders to ensure that the quality metrics is reviewed, closed and agreed upon. Create a list of milestones and checkpoints and set measurable criterias to check the quality on timely basis.
  • Defining Testing Strategies
  • Defining processes for test plan and several phases of testing cycle. Planning and scheduling several milestones and tasks like alpha and beta testing. Ensuring all development tasks meet quality criteria through test planning, test execution, quality assurance and issue tracking. Work closely on the deadlines of the project Ensure, you are focusing on automation along with manual testing. Keep raising the bar and standards of all the quality processes with every project. Thinking of continuous innovation. Review test strategies and see that all the various kinds of testing like unit, functional, performance, stress, acceptance etc. are getting covered.
  • Managing Risks
  • Understanding and defining areas to calculate the overall risk to the project. Creating strategies to mitigate those risks and take necessary measures to control the risks. Communicating or creating awareness to all the stake holders for the various risks Understand & review the current risks and escalate.
  • Process improvements
  • Challenge yourself continuously to move towards automation for all daily works and help others in the automation. Create milestones for yearly improvement projects and set. Work with the development team to ensure that the quality engineers get apt support like automation hooks or debug builds where ever and whenever possible

Requirements:

  • 5-8 years of strong experience in QA/testing or application development
  • Strong in Database and ETL testing
  • Understanding of Big Data principles
  • Strong at preparing the test plan and ensure that test plans get reviewed by all stakeholders and strong in peer reviews.
  • Strong command of Essential technologies: SQL scripting, PL/SQL.
  • must have strong skills in writing complex and automated SQL scripts
  • ETL Testing from various feeds on server (S3, SQL ,HIVE, Data Bricks, Snow Flake) using different testing strategy to ensure the data quality and data consistency, timeliness
  • Hadoop & Big Data Concepts and Data validation on HIVE tables
  • Having knowledge on large-scale data processing languages like pyspark is a plus.
  • Knowledge of API Testing
  • Experience in Python (or other scripting languages)
  • Proficient with software development lifecycle (SDLC) methodologies like Agile, QA methodologies, defect management system, and documentation.
  • Experience in automation, automation frameworks and automation delivery preferred.
  • Good at setting Quality standards in various new testing technologies in the industry.
  • Experience with one of the major cloud providers AWS, Azure or GCP
  • Good at identifying and defining areas to calculate the overall risk to the project and Creating strategies to mitigate those risks and escalate as necessary.
  • Excellent analytical and communication skill is required
  • Experience in Data analysis & requirements validation

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