As a Data Engineer Intern, you will have the opportunity to gain hands-on experience in designing, developing, and maintaining data pipelines and supporting data infrastructure. You will work closely with experienced data professionals to ensure data is accurate, accessible, and reliable for analytics and business decision-making. This internship is an excellent opportunity to build practical skills in data engineering and modern data technologies while contributing to real business projects.

• Final-year Bachelor’s student or recent graduate in Computer Science, Information Technology, Data Science, Software Engineering, Mathematics, or a related field.
• Basic understanding of SQL and relational databases.
• Familiarity with at least one programming language (Python is preferred).
• Basic knowledge of data structures, algorithms, and database concepts.
• Understanding of ETL processes and data warehousing concepts is an advantage.
• Strong analytical and problem-solving skills.
• Eagerness to learn new technologies and work with large datasets.
• Good communication skills and the ability to work effectively in a team.
• English proficiency is an advantage.

• Opportunity to learn through hands-on experience in a professional environment.
• Gain practical knowledge and real-world experience in data engineering.
• Develop communication, collaboration, and problem-solving skills.
• Improve teamwork abilities by working with cross-functional teams.
• Receive guidance and support from experienced mentors.
• Opportunity to build a successful career within Bir Ecosystem.

• Assist in developing and maintaining data pipelines and ETL/ELT processes.
• Support the integration of data from multiple internal and external sources.
• Monitor data quality and troubleshoot data-related issues.
• Help optimize data processing workflows for efficiency and scalability.
• Collaborate with Data Engineers, Data Analysts, and other cross-functional teams.
• Participate in testing, documenting, and improving data solutions.
• Learn and apply best practices in data engineering, data governance, and database management.
• Support ad hoc data-related tasks and ongoing projects.

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