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Assist in designing, developing, and maintaining data pipelines and infrastructure that support analytics, business intelligence, and machine learning applications
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Support the development of ETL/ELT processes to collect, transform, and organize data from various sources
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Write and optimize SQL queries and Python scripts to support data processing, reporting, and analysis
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Collaborate with data engineers, software engineers, and analytics teams to improve data accessibility, quality, and reliability
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Help build and maintain data tools and dashboards that provide actionable insights into business and product performance
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Gain hands-on experience with cloud-based data infrastructure, data warehouses, and modern data processing technologies
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Assist in troubleshooting data pipeline issues, identifying performance improvements, and implementing solutions with guidance from senior engineers
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Participate in code reviews, technical discussions, and team meetings while learning engineering best practices
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Document data processes, workflows, and technical solutions to support ongoing development and knowledge sharing
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Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Software Engineering, Information Systems, or a related technical field
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Foundational knowledge of Python and SQL, including experience writing queries, manipulating data, or developing scripts through coursework, projects, or internships
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Basic understanding of databases, data structures, and data processing concepts
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Familiarity with ETL/ELT processes, data pipelines, or data warehousing concepts
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Interest in learning modern AI and data technologies such as Claude, Snowflake, BigQuery, Apache Spark, Flink, or Apache Airflow
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Strong analytical and problem-solving skills, with attention to detail and a willingness to learn
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Good communication and collaboration skills, with the ability to work effectively in a team environment
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A proactive attitude, intellectual curiosity, and enthusiasm for working with data and emerging technologies
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Previous technical projects, relevant coursework, or internship experience in data engineering, software development, or analytics is a plus, but not required