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Data Quality Engineer

4 months ago

Bengaluru, India SMC Squared India Full time

Organization: SMC2

Job Location: Bangalore

Experience: 3 - 6years

Primary skill: DBT, Snowflake, SQL and python


This position is responsible for ensuring the integrity, accuracy, and reliability of data within the organization. The Data Quality Engineer will lead data validation efforts during the Snowflake migration project and continue to help establish a sound data quality function for the organization moving forward.

Responsibilities:


Must be able to:

  • Data validation efforts during Snowflake migration
  • Contribute to the establishment of a Center of Excellence (COE) for data quality, including the creation of test cases, test plans, and quality assurance frameworks.
  • Conduct data profiling and analysis to identify inconsistencies, anomalies, and inaccuracies.
  • Collaborate with cross-functional teams to understand data requirements and translate them into comprehensive test strategies.
  • Develop and execute manual data validation procedures in the absence of automated testing tools.
  • Provide regular updates on data quality metrics, issues, and resolutions to stakeholders.
  • Ensure compliance with data privacy regulations and organizational standards.


Required Knowledge, Skills, and Experience:

  • Strong proficiency in SQL for data validation and quality assessment.
  • Experience in writing clear, concise, and comprehensive test plans and test cases (manual & test automation)
  • Ability to quickly understand data domains and develop a test strategy.
  • Extensive experience in testing data pipelines on snowflake.
  • Experience in data preparation and testing with large volumes of data.
  • Strong verbal and written communication skills in preparing and sharing quality metrics with test results.
  • Knowledge of test automation tools and frameworks for data validation.
  • Experience working with cloud technologies like Snowflake on Microsoft Azure, Amazon AWS or Google GCP
  • Experience validating data pipelines involving tools and technologies such as AWS, Snowflake, Spark, Kafka