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Strong employer brand plus metro location and mid-level experience range increases applicant density moderately.
Data engineering skills (ETL, SQL, Python, cloud) are broadly transferable across industries.
Explicit degree enrollment, a mandatory 1–6 years experience band, and required technical skills make filters moderately strict.
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Collect, clean, transform, and validate large datasets from diverse sources using Python, SQL, and data-engineering tools.
Build and maintain ETL/ELT pipelines and support feature engineering and generative AI pipelines in collaboration with cross-functional teams.
Gain hands-on experience in data migration and modernization of a global procurement digital platform (STEP) including agile delivery and stakeholder coordination.
Currently enrolled or in final year of undergraduate or postgraduate degree in IT, Computer Science, Software Engineering, Information Technology, or Data Science/Analytics.
1–6 years of relevant professional experience.
Proficiency in Python, SQL, Git, ETL/ELT concepts, APIs, cloud platforms, and basic machine learning.
Proficiency in English language.
Experience or strong interest in data engineering within global development or complex, multi-stakeholder environments.
Comfortable working with large datasets on platforms like Snowflake, Databricks, Spark, or cloud services.
Familiar with agile processes, data governance, QA, and UAT preparation for digital platform modernization projects.