Data Engineering

Responsibilities:
Perform data analysis, transformation, and optimization using tools such as SQL, Python, and PySpark.
Build scalable, efficient, and reliable data pipelines to support ETL/ELT processes, data integration, and migration workflows.
Collaborate with cross-functional teams to design and deliver analytics solutions that support business decision-making.
Work with cloud-based data platforms like Snowflake to manage, process, and analyze large-scale datasets.

Qualifications:
Currently pursuing a Bachelor s or Master s degree in Computer Science, Data Engineering, or a related technical field.
Solid understanding and hands-on familiarity with Python and SQL for data manipulation, transformation, and automation.
Familiarity with modern data stack tools such as Apache Airflow, Snowflake, Apache Spark, and DBT.
Comfortable working with data visualization tools like Tableau to support reporting and insights generation.
Basic awareness of machine learning concepts, with exposure to MLOps and/or DevSecOps practices.
Strong communication skills with the ability to explain technical concepts to non-technical stakeholders.
Strong analytical thinking and problem-solving abilities, with attention to performance and data quality.

Duration: 10 to 12 weeks
Start Term: End of May (Flexible)