DQ Engineer Intern

We are looking for a motivated and detail-oriented Data Quality Engineer Intern to join our team. In this role, you will support the development and maintenance of data quality processes that ensure the accuracy, consistency, completeness, and reliability of data across our systems. You will work closely with data engineers, analysts, and business stakeholders to identify data issues, perform validation checks, and contribute to the continuous improvement of data quality standards.

This internship offers an excellent opportunity to gain hands-on experience with data quality frameworks, data analysis techniques, and modern data platforms while developing practical skills in data governance and quality assurance. You will participate in real-world projects, learn industry best practices, and help build trustworthy data solutions that support business decision-making.

The ideal candidate is curious, analytical, and eager to learn, with a strong interest in data engineering, quality assurance, and problem-solving.

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• Currently studying or recently graduated in Computer Science, Information Technology, Mathematics, Statistics, or a related field 
• Basic knowledge of SQL (SELECT, JOIN, GROUP BY, filtering) 
• General understanding of databases (Oracle, PostgreSQL, or similar) 
• Strong analytical thinking and high attention to detail, with the ability to spot patterns and anomalies in data.  
• Eagerness to learn, a proactive attitude, and the ability to work as part of a team. 

 

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Opportunity to learn through working

Gaining practical knowledge and experience

Development of communication and customer service skills

Improving teamwork abilities

Support from a professional mentor

Chance to build a future career at Bir Ecosystem

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• Perform data profiling to identify anomalies, errors & inconsistencies 
• Assist in preparing and executing data quality checks & business rules and ensure automated monitoring. 
• Collaborate with Data Governance team to support data quality standards & compliance 
• Investigate data quality issues, perform root-cause analysis and support their resolution 
• Prepare reports and dashboards on data quality metrics and trends 

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